statistics chapter 3 & 4

Statistics -- Chapter 3

summarizing data

Perimeter -- a descriptive measure of a population

statistic -- a descriptive measure of a sample

arithmetic mean -- a variable is computed by determining the sum of all the values of the variable in the data set, divided by the number of observations.

Population arithmetic mean (called a mew) -- is computed using all the individuals in a population. The population mean is a perimeter

sample arithmetic mean (called x-bar) -- is computed using sample data. The sample mean is a statistic

median -- this variable is the value that lies in the middle of the data when a range in ascending order. Half the data are below the median and half the data are above the median. We use M. to represent the median

mode -- a variable is the most frequent observation of the variable that occurs in the data said

bimodal -- the data set has two modes

compute the range of the variable from raw data

the simplest measure of dispersion is the range. To compute the range, the data must be quantitative.

The range, R, of a variable is the difference between the largest data value and the smallest data value.

Range = R = largest data value - smallest data value

Population variance -- the population variance of a veritable is the sum of the squared deviations about the population mean divided by the number of observations in the population

computational formula -- determines the population variance

bias -- overestimate and underestimates in a perimeter

weighted mean -- the weight did mean of the variable is found by multiplying each value of the variable by its corresponding weight, summing these products, and dividing the result by the sum of the weights

Z. score -- represents the distance that a data value is from the mean in terms of the number of standard deviations. It is obtained by subtracting the mean from the data value and dividing this result by the standard deviation

Summary

Measures of central tendency are used to indicate the typical value and a distribution. The mean measures the center of gravity of the distribution. The median separates the bottom 50% of the data for the top 50%. Both measures require that the data be quantitative. The mode measures the most frequent observation. The data can be either quantitative or qualitative to compute the mode. The median is resistant to extreme values, while the mean is not. A comparison between the median and the mean can help determine the shape of the distribution.

Measures of dispersion described the spread in the data. The range is the difference between the highest and lowest data value. The variance measures the average square deviation about the mean. The standard deviation is the square root of the variance. The mean and standard deviation are used in many types of statistical interference.

The mean, median, and measured can be approximated from grouped data. The variance and standard deviation can also be approximated from grouped data.

We can determine the relative position of any observation and a data set using Z- scores and percentiles. Z- scores denote how many standard deviations on observations is from the mean. Percentiles determine the percent of observations that lie above and below observation. The upper and lower fences can be used to identify potential outliers. Any potential outlier must be investigated to determine whether it was the result of a data entry air or, some other error in the data collection process, or of an unusual value in the data set.

The interquartile range is also a measure of dispersion. The five number summary provides an idea about the center and spread of a data set, through the median and the interquartile range. The length of the tales in the distribution can be determined from the smallest and largest data values. The five number summary is used to construct box plots. Box plots can be used to describe the shape of the distribution.

Statistics -- Chapter 4

relations between variables

Response variable -- the variable whose value can be explained by the value of the explanatory or predictor variable

scatter diagram -- graph that shows the relationship between two quantitative variables measured on the same individual. Each individual in the data set is represented by a point in the scatter diagram. The explanatory variable is plotted on the horizontal axis and the response variable is plotted on the vertical axis. Do not connect the points when drawing a scatter diagram

least squares regression criterion -- the least squares regression line is the one that minimizes the sum of the squared errors (or residuals). It is the line that minimizes the square of the vertical distance between the observed values and those predicted by the line

coefficient of determination -- measures the percentage of total variation in the response variable that is explained by the least squares regression line

Summary

the first step in identifying the type of relation that might exist is to draw a scatter diagram. The explanatory variable is plotted on the horizontal axis and the corresponding response terrible on the vertical axis. The scatter diagram can be used to discover whether the relation between the explanatory and the response variables is linear. In addition, for linear relations, we can judge whether the linear relationship is positive or negative association.

A numerical measure for the strength of linear relation between two quantitative variables is the linear correlation coefficient. It is a number between -- 1 and 1, inclusive. Values of the correlation coefficient near -- 1 are indicative of a negative linear relation between the two variables. Values of the correlation coefficient near +1 indicate a positive linear relation between the two variables. If the correlation coefficient is near zero, then there is little linear relation between the two variables.

Once a linear relation between the two variables has been discovered, we describe the relation by finding the least squares regression line. This line best describes the linear relation between the explanatory and the response variables. We can use the least squares regression line to predict a value of the response terrible for a given value of the explanatory variable.

Whenever a least squares regression line is obtained, certain diagnostics must be performed. These include verifying that the residuals have constant variance, verifying that the linear model is appropriate, and checking for outliners and influential observations.

What I worth mentioning again is that a researcher should never claim causation between two variables in a study unless the data are experimental. Observational data allows us to say that two variables might be associated, but we cannot claim causation.

Statistics -- Chapter 2

organizing and summarizing data

Frequency distribution -- lists each category of data and the number of occurrences for each category of data
relative frequency -- the proportion (or percent) of observations in the category and is found using the formula = = relative frequency equals frequency divided by some of all frequencies
relative frequency distribution -- lists each category of data together with the relative frequency
bar graph -- constructed by labeling each category of data on a horizontal axis in the frequency or relative frequency of the category on the vertical axis. Rectangles of equal with are drawn for each category. The height of each rectangle is equal to the category's frequency or relative frequency
pareto chart -- a bar graph news bars are drawn in decreasing order of frequency or relative frequency
pie chart -- a circle divided into sectors. Each sector represents a category of data. The area of each sector is proportional to the frequency of the category
histogram -- constructed by trawling rectangles for each class of data. The height of each rectangle is the frequency or relative frequency of the class. The width of each rectangle is the same in the rectangles touch each other
classes -- categories of data created by using intervals of numbers
lower class limit -- smallest value within the class
upperclass limit -- largest value within the class
class width -- difference between consecutive lower class limits
open ended -- first class has no lower limit or the last classes not have an upperclass limit
stem and leaf plot -- another way to represent quantitative data graphically
dot plot -- drawn by placing each observation horizontally in increasing order and placing a dot above the observation each time it is observed
class midpoint -- found by adding consecutive lower class limits and dividing the result by two
frequency polygon -- drawn by plotting a point above each class midpoint on a horizontal axis at a height equal to the frequency of the class. After the points for each class are plotted, straight lines are drawn between consecutive points
cumulative frequency distribution -- displays the aggregate frequency of the category. For discrete data, it displays the total number of observations less than or equal to the category. For continuous data, it displays the total number of observations less than or equal to the upperclass limit of a class
cumulative relative frequency distribution -- displays the proportion (or percentage) of observations less than or equal to the category for discrete data and the proportion of observations less than or equal to the upper class limit for continuous data
ogive -- a graph that represents the cumulative frequency or cumulative relative frequency for the class. It is constructed by plotting points whose x- coordinates are the upperclass limits and whose y-coordinates are the cumulative frequencies or cumulative relative frequencies. After the points for each class are plotted, straight lines are drawn between consecutive points
time-series data -- value of the variable is measured a different point in time
time-series plot -- obtained by plotting the time in which a variable is measured on the horizontal axis and the corresponding value of the variable on the vertical axis. Lines are then drawn connecting points

Summary
raw data are first organized into tables. Data are organized by creating classes into which they fall. Qualitative data and discrete data have values that provide clear-cut categories of data. However, with continuous data the categories, called classes, must be created. Typically, the first table created is a frequency distribution, which lists the frequency with which each class of data occurs. Other types of distributions include the relative frequency distribution and the cumulative frequency distribution.

Once data are organized into the table, graphs are created. For data that are qualitative, we can create bar charts and pie charts. For data that are quantitative, we can create histograms, stem and leaf plots, frequency polygons, and ogives.

Statistics Chapter 1 -- data collection

Statistics -- the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions
descriptive statistics -- consists of organizing and summarizing the information collected
inferential statistics -- methods that takes results obtained from a sample, extends them to the population, and measures the reliability of the result
qualitative or categorical variables -- allow for classification of individuals based on some attribute or characteristic
quantitative variables -- provide numerical measures of individuals. Arithmetic operations such as addition and subtraction can be performed on the values of a quantitative variable and will provide meaningful results
variables -- the characteristics of the individuals within the population
approach -- a way to look at and organize a problem so that it can be solved
discrete variable -- a quantitative variable that has either a finite number of possible values or a countable number of possible values. The term countable means that the values result from counting, such as 0, 1, 2, 3, and so on
continuous variable -- is a quantitative variable that has an infinite number of possible values that are not countable
Census -- a list of all individuals in a population along with certain characteristics of each individual
observational study -- measures the characteristics of the population by studying individuals in the sample, but does not attempt to manipulate or influence the variables of interest
designed experiment -- applies a treatment to individuals (referred to as experimental units or subjects) and attempts to isolate the effects of the treatment on a response variable
lurking variables -- characteristics that may be related to an outcome but not identified in the study
stratified sample -- obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each stratum should be homogeneous (or similar) in some way
systematic sample -- obtained by selecting every kth individual from the population. The first individuals selected corresponds to a random number between one and k
cluster sample -- obtained by selecting all individuals within a randomly selected collection or group of individuals
convenience sampling -- a sample in which the individuals are easily obtained
nonsampling errors -- errors is that result from the survey process. They are due to the nonresponse of individuals selected to be in the survey, to an accurate responses, too poorly worded questions, to bias in the selection of individuals to be given the survey, and so on
sampling error -- error that results from using sampling to estimate information regarding a population. This type of error occurs because a sample gives incomplete information about the population
designed experiment -- a controlled study conducted to determine the effect that varying one or more explanatory variables house on a response variable. The explanatory variables are often called factors. The response Venerable represents the veritable of interest. Control, manipulation, randomization, and replication by the key ingredients of a well designed experiment
treatment -- any combination of the values of each factor
experimental unit/subject -- person, object, or some other well defined item to which a treatment is applied
double-blind -- neither the experimental unit nor the experimenter knows what treatment is being administered to the experimental unit
placebo -- innocuous medication with no medicinal value
completely randomized design -- 1 in which each experimental unit is randomly assigned to a treatment
matched pairs design -- an experimental design in which the experimental units are paired up. The pairs are matched up so that they are somehow related. There are only two levels of treatment in a matched pair design
block -- each group of homogeneous individuals
blocking -- grouping similar homogeneous experimental units together and then randomizing the experimental units within each group to a treatment
confounding -- occurs when the effect of two factors on the response variable cannot be distinguished
randomized block design -- used when the experimental units are divided into homogeneous groups called blocks. Within each block, the experimental units are randomly assigned to treatments


Summary
we defined statistics of the science in which data are collected, organized, summarized, and analyzed to and for characteristics regarding a population. Descriptive statistics consists of organizing and summarizing information, while inferential statistics consists of drawing conclusions about population based on results obtained from a sample. The population is a collection of individuals on which the study is made, and the sample is a subset of the population.

Data are the observations of a variable. Data can either be qualitative or quantitative. Quantitative data are either discrete or continuous.

Data can be obtained from four sources: a census, existing sources, survey sampling, or a designed experiment. A census will list all of the individuals in the population, along with certain characteristics. Do to the costs of obtaining a census, most researchers opts for obtaining a sample. In observational studies, the veritable of interest has already been established. For this reason, they are often referred to as ex post facto studies. Designed experiments are used when control of the individuals in the study is desired to isolate the affect of a certain treatment on the response variable.

Five sampling methods:
simple random sampling
stratified sampling
systematic sampling
cluster sampling
convenience sampling

Convenience sampling typically leads to an on representative sample and biased results.

Unit 4 - summary

Organization Structure

An organization’s structure is how it organizes itself to communicate, develop workflow, and outline the hierarchy of authority, which is often referred to as ”chain of command”. The chain of command is often depicted in an organization chart. There are a variety of organization structures, namely, simple, functional, divisional, matrix, and conglomerate. Whatever the structure, organizations adopt a structure to gets things done through others in an effective way to achieve corporate goals. It’s important that an organization chose the best structure for to accomplish their goal. In the case of Xerox Corporation, Xerox initially selected a matrix structure, but found it cumbersome to achieve its goals. Today, Xerox is structured into four strategic business units.

Communication

Communication is key to effecting change within an organization and promoting excellence in achieving its organizational goals. It encourages and motivates employees to perform well for the good of the organization. Organizations face challenges today that affect achieving those goals—new communication technologies, a diverse workforce, and a global marketplace. How well an organization overcomes these challenges will determine its business success. The success depends upon the effectiveness of communications from all persons within the organization—from the chief executive officer down to the employee on the shipping dock. This is illustrated below.




Organizational Structures

Environmental forces and technological factors influence an organization’s structure. It is a complex system that is also influenced by the organization’s strategic choices. There are a variety of structures that are adopted due to their unique strengths and weaknesses, although the traditional organization is structured by functions, products, or geographies. Managers need to think about adopting structures that address the complex business strategies that today’s global market entails, including e-business organizational structures.



Organizational Environment

Organizations cannot survive or grow without interacting with their environmental surroundings. The environment provides resources or raw materials to organizations, and receives output in return. Environments can be very different—unpredictable, highly diverse, and unstable. Organizations must cope with rapidly-changing markets and technologies. If an organization’s environment is uncertain, then it must be flexible and have the ability to adapt to changing markets or other environmental factors very quickly. For example, when the computer was introduced for business use, many firms quickly developed departments responsible for managing information services. To prevent environmental turbulence from impacting an organization’s core business, organizations develop buffer departments to deal with these interferences, such as Corporate Communications or Legal departments.


Organizational Technology

The business world has become a smaller place with the advent of organizational technology. Why? Technology is used to communicate with employees, to service clients or customers, and to disseminate training to employees and customers more rapidly and anywhere in the world. Organizational technology adds value creation—it increases an organization’s Return on Investment, although organizations currently communicate with employees and customers. Organizations become more flexible and responsive. Organizational technology:

Improves process—system efficiencies are developed versus improving individual efficiencies
Allows more customer intimacy, meaning there are more opportunities for cross selling, managing customer databases, and specific customers can be targeted for marketing purposes
Maximizes technology for developing new ideas

Organizational behavior chapter 17

Organizational culture -- the set of shared values, beliefs, and norms that influences the way employees think, feel, and behave toward each other and toward people outside the organization values -- general criteria, standards, or guiding principles that people used to determine which types of behaviors, events, situations, and outcomes are desirable or undesirable
terminal value -- a desired end, State, or outcome that people seek to achieve
instrumental value -- a desired mood or type of behavior that people seek to follow
organizational ethics -- the moral values, beliefs, and rules that establish the appropriate way for an organization and its members to deal with each other and with people outside the organization
whistleblowing -- when an employee decides to inform an outside person or agency about illegal or unethical managerial behavior

Summary
Organizational culture is an important means through which organizations corny and motivate the behavior of their members. An organization can shape work attitudes and behaviors by the way it invests in and rewards employees overtime and by its attempts to encourage values of excellence.

Organizational culture is the set of shared values, beliefs, and norms that influences the way employees think, feel, and behave toward each other and toward people outside the organization.

There are two kinds of organizational values: terminal (a desired outcome) and instrumental (a desired mode of behavior). Ideally, instrumental values help the organization to achieve its terminal values.

Culture is transmitted to an organization's members by means of socialization and training programs and stories, ceremonies, and language used by members of the organization.

Organizational culture develops from the interaction of four factors:
the personal and professional characteristics of people within the organization
organizational ethics
the nature of the employment relationship between a company and its employees
and the design of its organizational structure.
These factors work together to produce different cultures and different organizations and caused changes in culture over time.

Different organizations have different kinds of cultures because they attract, select, and retained different kinds of people. Because of the organization's founder is instrumental in initially determining what kind of people get selected, a founder can have a long-lasting effect on an organization's culture.

Ethics are the moral values, beliefs, and rolls that establish the right or appropriate ways in which one person or group should interact in deal with another person or group. Organizational ethics are a product of societal, professional, and individual ethics.

The nature of the employment relationship between the Company and its employees causes the development of particular norms, values, and attitudes toward the organization.

Different organizational structures give rise to different patterns of interaction among people. These different patterns lead to the formation of different organizational cultures.

Adaptive cultures are those whose values and norms help an organization to build momentum and to grow and change as needed to achieve its goals and be effective. In our cultures are those that lead to values and norms that fail to motivate or inspire employees; they lead to stagnation and often failure over time.

Another important determinant of organizational culture is the values of the nation in which a company is founded and has its home operations.

A company can help to build and sustain an ethical culture by establishing the right kinds of incentives and rules for rewarding ethical behavior, by establishing a strong board of directors, and by making sure employees follow the legal rules and guidelines established by government agencies and watched by consumer groups.

Organizational behavior chapter 16

Organizational structure -- the formal system of task and reporting relationships that controls, coordinates, and motivates employees so that they cooperate and work together to achieve an organization's goals
organizational design -- the process by which managers select and manage various dimensions and components of organizational structure and culture so that an organization can achieve its goals
contingency theory -- organizational structure should be designed to match the set of contingencies -- factors or conditions -- that cause an organization the most uncertainty
technology -- a combination of skills, knowledge, tools, machines, computers, and equipment used in the design, production, and distribution of goods and services
small batch technology -- a method used to produce small quantities of customized, one-of-a-kind products based on the skills of people who work together in small groups
Mass production technology -- a method of production using automated machines that are programmed to perform the same operations time and time again
continuous process technology -- a method of production involving the use of automated machines working in sequence and controlled through computers from a central monitoring station
organic structure -- an organizational structure designed to promote flexibility so that employees can initiate change and adapt quickly to changing conditions
machanistic structure -- an organizational structure designed to induce employees to behave in predictable, accountable ways
function -- a set of people who perform the same types of tasks err hold similar positions in an organization
functional structure -- an organizational structure that groups together people who hold similar positions, perform a similar set of tasks, or use the same kinds of skills
division -- a group of functions created to allow an organization to produce and dispose of its goods and services to customers
product structure -- a divisional organizational structure that groups functions by types of product so that each division contains the functions it needs to service the products it produces
market structure -- a divisional organizational structure that groups functions by types of customers so that each division contains the functions it needs to service a specific segment of the market
geographic structure -- a divisional organizational structure that groups functions by region said that each division contains the functions it needs to service customers and a specific geographic area
corporate management -- the set of managers whose responsibility is to supervise and oversee the divisional managers
matrix structure -- an organizational structure that simultaneously groups people by function and by product team
Authority -- the power that enables one person to hold another person accountable for his or her actions
hierarchy of authority -- an organization's chain of command that defines the relative authority of each level of management
span of control -- the number of employees who report to a manager
mutual adjustment -- the ongoing informal communication among different people and functions that is necessary for an organization to achieve its goals
integrating mechanisms -- organizing tools used to increase communication and coordination among functions and divisions
standardization -- the development of routine responses to reoccurring problems or opportunities
formalization -- they use of rules and standard operating procedures to control an organization's activities
virtual organization -- a company that operates largely using new information technology in which people in functions are linked through company intranets and databases
network structure -- a structural arrangement whereby companies outsource one or more of their functional activities to other specialist companies

Summary
Organizational structure affects how people and groups behave in an organization by providing a framework that shapes employee attitudes and behavior. Organizations need to create a structure that allows them to corny and motivate people, functions, and divisions affectedly.

Organizational structure is the formal system of task and job reporting relationships that determines how employees use resources to achieve organizational goals. Organizational design is the process of making the specific choices about tasks and job relationships that result in the construction of a particular organizational structure.

Contingency theory argues that an organization structure needs to be designed to fit or match the set of contingencies (factors or conditions) been affected the most and cause it the most uncertainty.
Three important contingency factors are:

• the organizational environment
• advances in technology
• organization human resources
  

The greater the level of uncertainty in the environment, the more complex its technology, and the more highly skilled its workforce, the more likely are managers to design an organic structure, one that is flexible and can change quickly. The more stable the environment, the less complex its technology, and the less skilled its workforce, the more likely an organization is to have a mechanistic structure, one that is formal, controlling, and designed to induce employees to behave in predictable, accountable ways.

The main structures the organizations used to differentiate their activities and to group people into functions or divisions are functional, product, market, geographic, and matrix structures. Each of these is suited to a particular purpose and has specific coronation and motivation advantages and disadvantages associated with it.

As organizations grow, problems of coordinating activities between functions and divisions arise.
Three methods organizations can use to solve coronation problems are:

• use the hierarchy of authority
• mutual adjustment
• and standardization.
  

To coordinate their activities, organizations develop a hierarchy of authority and decide how to allocate decision-making responsibility. Two important choices that they must make our how many levels to have in the hierarchy and how much authority to decentralize to managers throughout the hierarchy and how much to retain the top.

To coordinate their activities, organizations develop mechanisms for promoting mutual adjustment (the ongoing informal communication and interaction among people and functions). Mechanisms that facilitate mutual adjustment included: direct contact, liaison roles, teams and task forces, and cross functional teams.

Organizations that use standardization to coordinate their cavities developed programmed responses and written roles that specify how people in functions are to coordinate their actions to accomplish organizational objectives. Organizations can standardize their input, throughput, and output activities.

Organizational behavior chapter 15

Decision making -- the process by which members of an organization choose a specific course of action to respond to both opportunities and problems
non-programmed decision-making -- decision making in response to novel opportunities and problems
programmed decision-making -- decision making in response to recurring opportunities and problems
performance program -- a standard sequence of behaviors the organizational members followed routinely whenever they encounter a particular type of problem or opportunity
classical decision making model -- a prescriptive approach based on the assumptions that the decision maker has all the necessary information and will choose the best possible solution or response
administrative decision-making model -- a descriptive approach stressing that incomplete information, psychological and social illogical processes, and a decision makers cognitive abilities affect decision-making and that decision makers often to satisfactory, not optimal, solutions
satisficing -- searching for and choosing an acceptable response or solution, not necessarily the best possible one
bounded rationality -- an ability to reason that is constrained by the limitations of the human mind itself
heuristics -- rules of thumb that simplify decision-making
availability heuristic -- the rule of thumb that says an event that is easy to remember is likely to have occurred more frequently than an event that is difficult to remember
representativeness heuristic -- the role of thumb that says similar kinds of events that happened in the past are a good predictor of the likelihood of an upcoming event
base rate -- the actual frequency with which an event occurs
anchoring and adjustment heuristic -- the rule of thumb that says that decisions about how big or small an amount (such as the salary, budget, or level of costs) should be/can be made by making adjustments from some initial amount
escalation of commitment -- the tendency to invest additional time, money, or effort into what were essentially bad decisions or unproductive courses of action
sunk costs -- costs that cannot be reversed and will not be affected by subsequent decision-making
groupthink -- a pattern of faulty decision-making that occurs in cohesive groups whose members strive for agreement at the expense of accurately assessing information relevant to the decision
Devils Advocate -- someone who argues against a cause or position in order to determine its validity
brainstorming -- a spontaneous, participated decision-making technique that groups use to generate a wide range of alternatives from which to make a decision
production blocking -- loss of productivity in brainstorming groups due to various distractions and limitations inherent to brainstorming
nominal group technique (NGT) -- a decision-making technique that includes the following steps: group members generate ideas on their own and write them down, group members communicate their ideas to the rest of the group, and each idea is then discussed and critically evaluated by the group
Delphi technique -- a decision-making technique in which a series of questioning errors is sent to experts on the issue at hand, who never actually meet face-to-face
benchmarking -- selecting a high performance group and using this group as a model
empowerment -- the process of giving employees throughout organization the authority to make decisions and be responsible for their outcomes
organizational learning -- the process through which managers seek to increase organization members desire and ability to make decisions that continuously raise organizational of fish and sea and effectiveness
exploration -- learning that involves organizational member searching for and experimenting with new kinds or forms of organizational behaviors and procedures to increase effectiveness
exploitation -- learning that involves organizational members finding ways to refine and improve existing organizational behaviors and procedures to increase effectiveness
learning organization -- an organization that purposefully take steps to enhance and maximize the potential for explorative and exploitative organizational learning to take place

Summary
The decisions made by employees at all levels and organizations can have major impact on levels of performance and well-being on the extent to which individuals, groups, and whole organizations achieve their goals.

The decision-making is the process by which members of an organization choose how to respond to opportunities and problems. Not programmed decision-making occurs when members of an organization choose how to respond to novel opportunities and problems. Not programmed decision-making involves a search for information. Programmed these fission making occurs when members of an organization respond to recurring opportunities and problems by using standard responses.

The classical model of decision-making is a prescriptive model that assumes that decision makers have access to all the information they need and will make the best decision possible.

A decision maker using the classical model takes these four steps:

• listing all alternatives
• listing the consequences of each alternative
• considering his or her preference for each alternative or set of consequences
• selecting the alternative that will result in the most preferred set of consequences.

Decisions made according to the classical model are optimal decisions.

There are problems with the classical model because it is not realistic. D. session makers often do not know all the alternatives they can choose from, often do not know the consequences of each alternative, may not be clear about their own preferences, and in many cases lack the mental ability to take into account all the information required by the classical model. Moreover, the classical model can be very time-consuming.

March and Simon's administrative decision-making model is descriptive; it explains how decisions are actually made in organizations. March and Simon propose that decision makers choose how to respond to opportunities and problems on the basis of a simplified and approximate account of the situation called the decision makers definition of the situation. This definition is the result of both psychological and sociological processes. Rather than making optimal decisions, decision makers often satifice, or make unacceptable decision, not necessarily an optimal decision. Satisficing occurs because of bounded rationality.

Heuristics are rules of thumb that simplify decision-making but can lead to errors or biases. The availability heuristic reflects the tendency to determine the frequency of an event and its causes by how easy they are to remember. The availability heuristic can lead to biased decision-making when the frequency of an event and causes is overestimated because they are vivid, extreme, or recent. The representativeness heuristic reflects the tendency to predict the likelihood of an event from the extent to which the event is typical of similar kinds of events that happened in the past.

Representativeness can lead to biased decision-making when decision-makers fail to take into account base rates. The anchoring and adjustment heuristic reflects the tendency to make decisions based on adjustments from some initial account. The anchoring and adjustment heuristic can lead to biased decision-making when the initial amounts were too high or too low.

Escalation of commitment is the tendency of decision-makers to invest additional time, money, or effort into losing courses of action. Escalation of commitment occurs because decision-makers do not want to admit that they have made a mistake, view further commitment of resources as a way to recoup sunk costs, and no more likely to take risks when decisions are framed in negative rather than positive terms.

The advantages of using groups instead of individuals to make decisions include the availability and diversity of members skills, knowledge, and expertise; enhanced memory for facts; capability of air or detection; and greater decision acceptance. The disadvantages of group decision-making include the time it takes to make a decision and the potential for groupthink. Other consequences include diffusion of responsibility, group polarization, and the potential for conflict.

Group decision-making techniques used in organizations include brainstorming, the nominal group technique, and the Delphi technique. Two group decision-making techniques used in total quality management are benchmarking and empowerment.

Two main types of organizational learning that can lead to improve decision-making all our explorative and exploitative learning. Organizations can improve their members ability to make high-quality decisions by encouraging them to develop personal mastery and complex mental models through team learning, by building a shared vision, and through systems thinking.