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Statistics

Learning Objectives. 1.Define Statistics2.Describe the Uses of Statistics3.Distinguish between Descriptive

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Statistics

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    1. Statistics Statistics, Data, & Statistical Thinking Chapter 1

    2. Learning Objectives 1. Define Statistics 2. Describe the Uses of Statistics 3. Distinguish between Descriptive & Inferential Statistics Define Population, Sample, Parameter, & Statistic Learn data types / collection methods

    3. What Is Statistics? 1. Collecting Data e.g. Survey 2. Presenting Data e.g., Charts & Tables 3. Characterizing Data e.g., Average :1, 1, 3:1, 1, 3

    4. Statistics Defined Statistics is the science of data that involves: Collecting Classifying Summarizing Organizing and Interpreting numerical information.

    5. Statistical Methods

    6. Application Areas Economics Forecasting Demographics Sports Individual & Team Performance Engineering Construction Materials Business Consumer Preferences Financial Trends

    7. Methods Defined

    8. Descriptive Statistics 1. Involves Collecting Data Presenting Data Characterizing Data 2. Purpose Describe Data

    9. Inferential Statistics 1. Involves Estimation Hypothesis Testing 2. Purpose Make Decisions About Population Characteristics

    10. Key Terms 1. Population (Universe) All Items of Interest 2. Sample Portion or subset of a Population 3. Parameter Summary Measure about Population 4. Statistic Summary Measure about Sample Data facts or information that is relevant or appropriate to a decision maker Population the totality of objects under consideration Sample a portion of the population that is selected for analysis Parameter a summary measure (e.g., mean) that is computed to describe a characteristic of the population Statistic a summary measure (e.g., mean) that is computed to describe a characteristic of the sample Data facts or information that is relevant or appropriate to a decision maker Population the totality of objects under consideration Sample a portion of the population that is selected for analysis Parameter a summary measure (e.g., mean) that is computed to describe a characteristic of the population Statistic a summary measure (e.g., mean) that is computed to describe a characteristic of the sample

    11. More Key Terms Variable Property of an individual population unit 2. Measurement Process that assigns numbers to variables Census Measuring variable for every unit in the population

    12. Key Terms 1. Population (Universe) All Items of Interest 2. Sample Portion of Population 3. Parameter Summary Measure about Population 4. Statistic Summary Measure about Sample Data facts or information that is relevant or appropriate to a decision maker Population the totality of objects under consideration Sample a portion of the population that is selected for analysis Parameter a summary measure (e.g., mean) that is computed to describe a characteristic of the population Statistic a summary measure (e.g., mean) that is computed to describe a characteristic of the sample Data facts or information that is relevant or appropriate to a decision maker Population the totality of objects under consideration Sample a portion of the population that is selected for analysis Parameter a summary measure (e.g., mean) that is computed to describe a characteristic of the population Statistic a summary measure (e.g., mean) that is computed to describe a characteristic of the sample

    13. Reliability A measure of reliability is a statement – usually quantified – about the degree of uncertainty associated with a statistical inference.

    14. Four Elements of Descriptive Statistics Problems The population or sample of interest One or more variables to be investigated Tables, graphs and numeric summary tools Identification of patterns in the data

    15. Five Elements of Inferential Statistics Problems The population of interest One or more variables to be investigated Sample of population units Inference about population based on the sample results Measure of reliability for the inference

    16. Types of Data

    17. Quantitative Data Measurements recorded on a naturally occurring numerical scale. Interval Data No common ‘0’ point Ratio Data Origin (0) is meaningful and consistent

    18. Qualitative Data Measurements that do not exist on any naturally occurring numerical scale; they can only classified into categories. Nominal Numeric codes Ordinal Arbitrary numeric ranking scale

    19. How to Obtain Data Published source Designed experiment Survey Observational study

    20. A Word About Samples Representative Exhibits characteristics typical of the target population Random Each element has an equally likely chance of being selected

    21. Statistical Computer Packages 1.Typical Software SAS SPSS MINITAB Excel 2. Need Statistical Understanding Assumptions Limitations

    22. Expert Commentary

    23. Conclusion 1. Defined Statistics 2. Described the Uses of Statistics 3. Distinguished Descriptive & Inferential Statistics Defined Population, Sample, Parameter, & Statistic Discussed data types/collection methods

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