the power of statistics coursera weekly challenge 5 answers

Test your knowledge: Introduction to hypothesis testing

1. Fill in the blank: The _____ typically assumes that observed data does not occur by chance.

  • subjective hypothesis
  • objective hypothesis
  • null hypothesis
  • alternative hypothesis

2. Which of the following statements describe significance level? Select all that apply.

  • Significance level is probability of rejecting the alternative hypothesis when it is true.
  • Significance level is the threshold at which a result is considered due to chance.
  • Significance level is the probability of rejecting a null hypothesis when it is true.
  • Significance level is the threshold at which a result is considered statistically significant.

3. What concept refers to the probability of observing results that are at least as extreme as those observed when the null hypothesis is true?

  • P-value
  • Statistical significance
  • Z-score
  • Confidence level

4. A data professional conducts a hypothesis test. They mistakenly conclude that their result is statistically significant when it actually occurred by chance. What type of error does this scenario describe?

  • Type I
  • Type II
  • Type III
  • Type IV

Test your knowledge: One-sample tests

5. In a one-sample hypothesis test, what does the null hypothesis state?

  • The population mean is equal to an observed value.
  • The population mean is not equal to an observed value.
  • The population mean is less than an observed value.
  •  The population mean is greater than an observed value.   

6. A data professional conducts a hypothesis test. They discover that their p-value is less than the significance level. What conclusion should they draw?

  • Decide the test is inconclusive.
  • Reject the alternative hypothesis.
  • Fail to reject the null hypothesis.
  • Reject the null hypothesis.

Test your knowledge: Two-sample tests

7. What does a two-sample hypothesis test determine?

  • Whether a sample statistic, such as a mean or proportion, is equal to a specific value
  • Whether two population parameters, such as two means or two proportions, are equal
  • Whether a population parameter, such as a mean or proportion, is equal to a specific value
  • Whether two sample statistics, such as two means or two proportions, are equal

8. What is the null hypothesis of a two-sample t-test?

  • There is no difference between two population means
  • There is no difference between two population proportions
  • The population proportion is equal to an observed value
  • The population mean is equal to an observed value

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Test your knowledge: Hypothesis testing with Python

9. A data professional can use the Python function scipy.stats.ttest_ind() to compute the p-value for the two-sample t-test.

  • True
  • False

10. What arguments of the Python function scipy.stats.ttest_ind(a, b, equal_var) refer to observations from the sample data? Select all that apply.

  • b
  • alpha
  • a
  • loc
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