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7.2 Hypothesis Testing for the Mean (Large Samples)

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7.2 Hypothesis Testing for the Mean (Large Samples). Key Concepts: Hypothesis Testing ( P -value Approach) Critical Values and Rejection Regions Hypothesis Testing (Critical-Value Approach). 7.2 Hypothesis Testing for the Mean (Large Samples).

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7 2 hypothesis testing for the mean large samples
7.2 Hypothesis Testing for the Mean (Large Samples)
  • Key Concepts:
    • Hypothesis Testing (P-value Approach)
    • Critical Values and Rejection Regions
    • Hypothesis Testing (Critical-Value Approach)
7 2 hypothesis testing for the mean large samples1
7.2 Hypothesis Testing for the Mean (Large Samples)
  • So how do we calculate the P-value of a test?
    • Recall: The P-value of a hypothesis test is the probability of obtaining a sample statistic with a value as extreme as or more extreme thanthe one determined from the sample data.
      • When we test for one population mean, we use the standardized version of the sample mean as our sample (or test) statistic.
    • Practice finding P-values:

#2 p. 389 (left-tailed test)

#6 (two-tailed test)

7 2 hypothesis testing for the mean large samples2
7.2 Hypothesis Testing for the Mean (Large Samples)
  • We are finally ready to conduct a hypothesis test for the mean using P-values! Guidelines are provided on page 381 (Using P-Values for a z-Test for the Mean µ).

#34 p. 391 (Sprinkler System)

#38 p. 392 (Salaries)

7 2 hypothesis testing for the mean large samples3
7.2 Hypothesis Testing for the Mean (Large Samples)
  • If the P-value of a test is difficult to calculate, we can use what’s known as the critical-value approach.
    • A rejection region of the sampling distribution is the range of values for which the null hypothesis is not probable.
    • A critical value separates the rejection region from the nonrejection region.
      • Practice finding critical values and rejection regions

#16 p. 390

#20

7 2 hypothesis testing for the mean large samples4
7.2 Hypothesis Testing for the Mean (Large Samples)
  • How do we decide whether or not to reject the null hypothesis when we’re working with critical values and rejection regions?
    • If our test statistic falls within the rejection region, we reject Ho. Otherwise, we do not reject Ho.
  • Guidelines are provided on page 386 (Using Rejection Regions for a z-Test for µ).

#40 p. 392 (Caffeine Content in Coffee)

#42 p. 393 (Sodium Content in Cereal)

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