Chapter 1: Data and Statistics 2023 with verified questions and answers

Statistics Can refer to numerical facts such as averages, medians, percent's, and index numbers that help us understand a variety of business and economic situations can also refer to the art and science of collecting analyzing and presenting interpreting data Data the facts and figures collected, analyzed, and summarized for presentation and interpretation Data Sets All the data collected in a particular study Elements The entities on which data are collected Variable A characteristic of interest for the elements Observation The set of measurements obtained for a particular element Scales of Measurement Include: Nominal, Interval, Ordinal, ratio Scales Determine the amount of information contained in the data, and indicates the data summarization and statistical analyses that are most appropriate Nominal Data are labels or names used to identify an attribute of the element, A non-numeric label or numeric code may be used Ordinal The data have the properties of nominal data and the order of rank of the data is meaningful A non-numeric label or numeric code may be used Interval The data have the properties of ordinal data and interval between observations is expressed in terms of fixed unit of measure ALWAYS numeric (the difference in scores example) (b-a= difference) Ratio The data has all the properties of interval data and the ratio of two values is meaningful Variables such as distance, height, weight, and time use the ratio scale Must contain a zero value indicating that nothing exist for the variable at that point (twice as much) Categorical Data Labels or names used to identify an attribute of each element Often referred to as qualitative data uses either nominal or ordinal scale of measurement can be either numeric or non-numeric Appropriate statistical analyses are rather limited Quantitative data Indicates how many or how much (discrete,continuous) ALWAYS numeric Ordinary arithmetic operations are meaningful for quantitative data Discrete Measure how many Continuous Measures how much Cross-Sectional Data collected at the same or approximately the same point in time Time Series Data Collected over several time periods helps analydtd understand: what happened in the past, identify any trends over time, and project future levels for the time series Data Sources Internal company records, Business database services, Government agencies, Industry associations, special interest organizations, internet Data Available from Internal Company Records Employee records, production records, inventory records, sales records, credit records, customer profile Data Available from Selected Government Agencies Census Bureau, Federal Reserve Board, Office of Mgmt&Budget, Department of Commerce, Bureau of Labor Statistics Experimental Studies The variable interest is first identified, Then one or more other variables are identified and controlled so that data can be obtained about how they influence the variable of interest Observational Studies (non-experimental) no attempt is made to control or influence the variables of interest (like a survey) Data Acquisition Considerations Time Requirement, Cost Acquisition, Data Errors Descriptive Statistics Most of the statistical information in newspapers, magazines, company reports, and other publications consists of data that are summarized and presented in a form that is easy to understand Such summaries of data, which may be tabular, graphical, or numerical, are refers to as descriptive statistics Tubular Summary NOT SURE WHAT THIS IS Graphical Summary I believe its just a graph but get clarification Numerical descriptive Statistics The most common numerical descriptive statistic is the average or mean (might need some clarification as well) Statistical Inference The process of using data obtained from a sample to make estimates and test hypothese about the characteristics of a population ex: Population, Census, Sample, Sample Survey, Population The set of all elements of interest in a particular study Census Collecting data for the entire population Sample A subset of the population Sample Survey Collecting data for a sample Process of Statistical inference 1. Population consists of all efficiency apartments. Average rent is unknown 2. A sample of 70 efficiency apartments is examined 3. The sample data provide an average rent of 490.80 4. The sample average is used to estimate the population average Data Warehousing Capturing, storing and maintaining the data, is a significant undertaking Data Mining Converting the data into a useful information, the most effective systems use automated procedures to discover relationships in the data and predict future outcomes Data Mining Applications Major applications of data mining have been made by companies with a strong consumer focus such as retail, financial and communication firms they also relate product to the consumer in order to predict future purchases like the what you might like section on a shopping page Data Mining Requirements Statistical Methodology such as multiple regression, logistic regression an correlation are heavily used, also needed are computer science technologies involving artificial intelligence and machine learning a significant investment in time and money as well Data mining Model Reliability A statistical model that works well with a particular sample may not work with another data can be divided into a training set and test set there is however a danger of over fitting the model to the point that misleading associations and conclusions appear to exist careful observations and extensive testing is important Ethical guidelines Strive to be fair thorough, objective and neutral as you collect, analyze, and present data As a consumer of statistics, you should also be aware of the possibility of unethical behavior by others The American Statistical Association