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Business Statistics Chapter Notes 1 Chapter 2 Data Statistics Descriptive Statistics coping with lots of numbers o Draw a picture graph charts etc o Calculate a few numbers which summarize the data mean median percentile Inferential Statistics o Making decisions and predictions about a population o Generalize facts from a sample to an entire population o Sampling is cheaper faster and more accurate Random Sampling Collect the five W s Who What Where When and Why Important if measured in a different time location and tell the difference between Data values or observations are information collected regarding some subject insight nonsense What is Data o Numbers names etc o Identifies the Who and What Useless without their context Data tables are used to help keep the information organized o Rows correspond to individual cases about Whom we record some characteristics Respondents individual s who answer a survey Subjects or Participants people in an experiments Experimental Units animals plants websites or other inanimate objects Variable the aspect characteristic that differs from subject to subject individual to individual Variables Each question measures some aspect of you o Age sex major Data the value of the variables o 20 Male English Identifies What has been measured usually shown on the columns Variable Types Categorical Variable a variable that names categories whether with words or numeral s o Descriptive responses to questions What kind of advertising do you use o Yes or No responses Quantitative Variable measured numerical values with units and variable that explains the quantity o Units yen cubits carats angstroms nanoseconds miles per house degrees Celsius 2 Qualitative or Categorical Variables Ordinal Variables categories that have a natural ordering o Numbers o Class such as Freshman Sophomore Junior Senior as 1 2 3 4 o Grades A B C D F GPA o Preference Strongly Agree Agree Disagree Strongly Disagree Nominal Variables categories that have no natural ordering o Major and Eye Color Two Types of Variables Quantitative or Numerical Variables o Numbers Measurements Age Height Miles traveled Qualitative or Categorical Variables o Classifying each observation o Sex Year in school major Discrete Variables natural gap between the values o of children credit cards o Whole s Continuous Variables values can be arbitrarily close together o Weight Height Age o Including decimal s Variable Types Counts natural way to summarize a categorical distribution of the variable or data values o Summary of the frequency of cases in a category o Values of a variable whose units are number of something Identifiers unique identifier assigned to each individual or item in a group o Social Security number student ID numbers tracking numbers Other Data Types Categorical Variables o Nominal Variables o Ordinal Values Examples 1 Appraisal of a company s inventory level excellent good fair poor Qualitative Ordinal 2 Mode of transportation to work Automobile bicycle bus subway walk Qualitative Nominal 3 Speed of a Vehicle Quantitative Continuous 4 of persons in each family Quantitative Discrete Interval Data no meaningful zero point Can t multiply or divide but the difference between two values is meaningful 3 o Temperature Ratio Data meaningful zero point can multiply and divide o Income weight height Time Series Data ordered data values over time o Measured at regular intervals over time o Example determining total costs each month of a year Cross Sectional Data data values observed at a single point in time o Several variables are all measured at the same time point o Determining sales revenue of customers and expenses for the last month of business Chapter 3 Surveys and Sampling Key Ideas 1 Examine a Part of the Whole o Draw a Sample o Goal learn about an entire population of individual s but examining all of them is not feasible o Sample study a smaller random group chosen from the population o Biased sample doesn t represent the population through over or underemphasize some characteristics Sources of Bias o Selection B difference between population of interest and effective population o Non Response B subjects don t answer or skip questions o Response B subjects lie or interviewer effect Telephone Poll B o Selection B cell phones or multiple phones o Non response B answering machines o Response B 2 Randomize o Gets rid of biases o Protect against factors that you know are in the data or unaware of o Makes sure that on the average the sample looks like the rest of the population Sampling Error Sample to sample differences 3 Sample Size Matters o Size of the sample matters not the size of the population Exception if population is small enough and the sample is more than 10 of the whole population then it may matter o Fraction of the population that you have sampled does not matter 4 Population vs Sample assess directly Population entire group of individuals in which we are interested but can t usually o Parameter describing a characteristic of the population Sample part of the population we actually examine for which we do have data o Statistic describing a characteristic of a sample Non statistical Sampling Convenience collected in the most convenient manner for the researcher o Bias opinions limited to individual s present Voluntary individual s choose to be involved o Bias different people are motivated to respond or not and systematically favors a particular outcome Inaccurate data Census an attempt to collect data on the entire population of interest Statistical Sampling chosen based on known or calculable probabilities Simple Random equal chance of being selected random generator o Sampling Frame a list of individual s from which the sample will be drawn effective population Stratified Random Sampling o Homogeneous Strata dividing the population into subgroups according to some common characteristics o Select a simple random sample from each subgroup o Combine samples from subgroups into one 5 Cluster Sampling o Divide population into several clusters each representative of the population such as county o Select a simple random sample of clusters Systematic Random Sampling o Decide on sample size n o Divide ordered frame of N individual s intro groups of k individual s k N n o Randomly select one individual from the 1st group and every kth individual afterwards Sample Survey designed to ask questions of a small group of people in order to learn something about entire Main Objective collect

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