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QBA 260

QBA 260. Chapter 1. Chapter 1 Topics. Samples and Populations Types of Data Variables – Independent and Dependent Probability Hypothesis Testing Types of Error Intro to Excel. Samples and Populations. Why do we sample? Examples of sampling What does “inferential statistics” mean?

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QBA 260

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  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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