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Understanding Statistics: Key Concepts in Samples, Populations, and Hypothesis Testing

This chapter provides a comprehensive overview of crucial statistical concepts including samples, populations, types of data, and the distinction between independent and dependent variables. Explore essential topics such as probability, hypothesis testing, and various types of errors—Type I and Type II. Learn about sampling methods, inferential statistics, and how to apply these concepts using Excel. This foundational knowledge is pivotal for anyone looking to grasp the basics of statistics and data analysis techniques effectively.

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Understanding Statistics: Key Concepts in Samples, Populations, and Hypothesis Testing

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Presentation Transcript

  1. QBA 260 Chapter 1

  2. Chapter 1 Topics • Samples and Populations • Types of Data • Variables – Independent and Dependent • Probability • Hypothesis Testing • Types of Error • Intro to Excel

  3. Samples and Populations • Why do we sample? • Examples of sampling • What does “inferential statistics” mean? • Terms: • Population – Parameters • Sample - Statistics

  4. Types of Data • Nominal • Ordinal • Interval • Ratio

  5. Variables • Variable = something that can take on more than one value • Independent → Dependent • Examples

  6. Probability • Probability = the chance of something happening • Probability = (number of ways the event can occur)/(total number of possible events) • What is the probability of getting a “head” if you flip a coin? • What is the probability of getting 2 fours if you roll two dice? • Conditional Probability – the chance of something happening given some condition

  7. Hypothesis Testing • Null Hypothesis (H0) – our machine is working correctly • Alternative Hypothesis (H1) – our machine is not working correctly • Choices: to reject H0 or not to reject H0

  8. Hypothesis Testing – Another Example • Let’s say there are 3 different teaching methods for a particular college course: • Full in-class • Full on-line • Combination of in-class and on-line • Null Hypothesis (H0) – Full in-class teaching is the best teaching method • Alternative Hypothesis (H1) – Full in-class teaching is not the best teaching method • Choices: If you reject H0 then you know that full in-class teaching is not the best method but you still do not know which of the other two methods is better

  9. Two types of Error • Type 1 Error – when you reject H0 and you should not have • (example: you rejected the hypothesis that the machine was working correctly and brought in the repair crew to fix it; however, the machine was working correctly to begin with) • Type II Error – when you do not reject H0 and you should have • (example: you did not reject the null hypothesis and assumed the machine was working correctly when it really was not)

  10. Chapter 1 • Switch to Excel

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