TERMS FOR BUSINESS STATISTICS descriptive statistics statistical procedures used to describe a population being studied only can be used to describe the group that is being studied non generalized inferential statistics making predictions or inferences about a population from observations and analyses of a sample generalize data values observations information collected regarding some subject data numbers names etc tells us the who and what respondents individuals who answer a survey subjects participants people in an experiment experimental units animals plants websites inanimate objects variable the aspect characteristic that differs from subject to subject individual to individual what is being measured columns data the value of the variables categorical qualitative variable when a variable names categories and answers questions about how cases fall into these categories sex year in school major descriptive responses to questions like what kind of advertising do you use with possible answers like newspapers internet direct mail may only have 2 possible values like yes and no ordinal variable categories that have a natural ordering numbers could be assigned to categories EX Class Rank 1 Freshman 2 Sophomore 3 Junior 4 Senior EX Grade A B C D F GPA EX Preference Strongly Agree Agree Disagree Strongly Disagree nominal variables categories that have no natural ordering EX Major business mathematics history EX Eye Color blue green brown numerical quantitative variable when a variable has measured numerical values with units and the variable tells us about the quantity of what is measured EX age height miles traveled discrete variables there is a natural gap between the values continuous variables the values can be arbitrarily close together EX of children EX of credit cards EX Weight EX Height EX Age identifier variable a unique identifier assigned to each individual or item in a group EX social security number student ID number tracking number transaction number interval data no meaningful zero point cant multiply or divide but the difference between 2 values is meaningful temperature ratio data time series data meaningful zero point can multiply and divide income weight height variables that are measured at regular intervals over time determining total costs each month of a year cross sectional data several variables are all measured at the same time point determining sales revenue number of customers and expenses for the last month of business Data Sources Where How When when data are collected can be important data that are decades old may mean something different than similar values recorded last year where data are collected can be important data collected in Mexico may differ in meaning than data collected in the US how data are collected can make the difference between insight and nonsense data that comes from a voluntary survey on the Internet are almost always worthless however data provided by agencies and businesses on websites can be extremely useful 1 Examine a Part of the Whole the first idea is to draw a sample goal learn about an entire population of individuals but examining all of them is not feasible sample is chosen from the population and examined samples that over under emphasize some characteristics of the population are said to be biased Bias sample doesn t represent population generalizations no longer valid conclusions may no longer be true Selection Bias problem in sampling scheme systematic tendency to exclude one kind of individual from the survey difference between population of interest and effective population EX cell phones multiple phones Non Response Bias subjects don t answer skip questions EX answering machines Response Bias subjects lie interviewer effect self selected sample more passionate more likely to respond minority opinion more passion opposite of the truth 2 Randomize randomization can protect you against factors that you know are in the data it can also help protect against factors you are not even aware of randomization gets rid of biases randomizing makes sure that on the average the sample looks like the rest of the population sampling error what sample to sample differences are referred to 3 Sample Size is What Matters it is the size of the sample not the size of the population that makes the difference in sampling the fraction of the population that you have sampled doesn t matter it is the sample size itself that is important population the entire group of individuals in which we are interested but can t usually assess directly EX all voters in US Visa card holders in DC all packages at a UPS center parameter a number describing a characteristic of the population sample the part of the population we actually examine and for which we do have data statistic a number describing a characteristic of a sample Sampling Techniques Nonstatistical Sampling convenience collected in the most convenient manner for the researcher ask whoever is around Bias opinions are limited to individuals present voluntary individuals choose to be involved very susceptible to being biased because different people are motivated to respond or not Often called public opinion polls these are not considered valid or scientific Bias sample design systematically favors a particular outcome Statistical Sampling Individuals in the sample are chosen based on known or calculable probabilities Simple random sampling SRS every possible sample of a given size has an equal chance of being selected draw names out of a hat use a random number table sampling frame list of population EX phone book registered voter list membership list stratified random sampling divide population into subgroups strata according to some common characteristic EX gender select a SRS from each subgroup and combine samples from subgroups into one cluster sampling divide population into several clusters each representative of the population EX county select a SRS of clusters all items in selected clusters can be used or items can be chosen from a cluster using another probability sampling technique systematic random sampling decide on sample size n divide ordered EX alphabetical frame of N individuals into groups of k individuals k N n randomly select one individual from the 1st group and select every kth individual thereafter exit polls 1 stratify on states 2 choose a SRS of polling places in each state number of polling places is proportional to the number of voters in each state 3 choose an
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