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

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

Weekly challenge 5

11. Which of the following statements accurately describe the null hypothesis? Select all that apply.

  • The alternative hypothesis typically assumes that observed data occurs by chance.
  • The alternative hypothesis typically assumes that observed data does not occur by chance.
  • The null hypothesis typically assumes that observed data does not occur by chance.
  • The null hypothesis typically assumes that observed data occurs by chance.

12. What claim states that the results of a test or experiment are not explainable by chance alone?

  • P-value
  • Statistical significance
  • Confidence level
  • Significance level

13. A data professional conducts a hypothesis test. They fail to reject the null hypothesis. What statement best describes their conclusion?

  • Their p-value is greater than their significance level.
  • Their p-value is greater than their confidence level
  • Their confidence level is greater than their p-value
  • Their significance level is greater than their p-value

14. Fill in the blank: A type I error is also known as a _____.

  • false negative
  • true positive
  • false positive
  • true negative

15. Fill in the blank: Rejecting or failing to reject the null hypothesis is the _____ step in conducting a hypothesis test.

  • first
  • second
  • third
  • fourth

16. A data professional conducts a hypothesis test. They choose a significance level of 5%. They calculate a p-value of 3.3%. What conclusion should they draw?

  • Reject the alternative hypothesis.
  • Reject the null hypothesis.
  • Fail to reject the null hypothesis.
  • Fail to reject the alternative hypothesis.

17. A data professional is conducting a two-sample t-test. What does their alternative hypothesis state?

  • There is no difference between two population means.
  • There is a difference between two population proportions.
  • There is no difference between two population proportions.
  • There is a difference between two population means.

18. A data professional conducts a hypothesis test to compare the mean annual sales of two different restaurants in the same restaurant chain. They write the following code:

scipy.stats.ttest.ind(a=530, b=550, equal_var=FALSE)

What does the argument b=550 refer to?

  • Significance level
  • Observations from the second sample
  • P-value
  • Whether or not the population variance of the two samples is assumed to be equal

19. To draw a conclusion about the null hypothesis, what two concepts are compared?

  • P-value and significance level
  • Alternative hypothesis and significance level
  • Confidence level and significance level
  • P-value and alternative hypothesis

20. A data professional conducts a hypothesis test. When they draw their conclusion, they commit a type I error. Which of the following statements describe their error? Select all that apply.

  • They fail to reject a null hypothesis that is actually false.
  • They reject a null hypothesis that is actually true.
  • They conclude their result is statistically significant when in fact it occurred by chance.
  • They fail to reject a null hypothesis that is actually false.

21. A data professional conducts a hypothesis test to compare the mean time customers spend on two different versions of a company’s website. To start, they state the null hypothesis and the alternative hypothesis. What should they do next?

  • Find the margin of error.
  • Choose a significance level.
  • Find the p-value.
  • Reject or fail to reject the null hypothesis.

22. A data professional is conducting a hypothesis test. Their null hypothesis states that there is no difference between two population proportions. What type of test are they conducting?

  • Two-sample z-test
  • Two-sample t-test
  • One-sample z-test
  • One-sample t-test

23. A data professional conducts a hypothesis test to compare the mean annual sales of two different restaurants in the same restaurant chain. They write the following code:

scipy.stats.ttest.ind(a=530, b=550, equal_var=FALSE)

What does the argument equal_var=FALSE refer to?

  • Observations from the first sample
  • P-value
  • Whether or not the population variance of the two samples is assumed to be equal
  • Significance level

24. Which of the following statements accurately describe the null hypothesis? Select all that apply.

  • The null hypothesis typically assumes that observed data occurs by chance.
  • The null hypothesis typically assumes that observed data does not occur by chance.
  • The null hypothesis is assumed to be true unless there is convincing evidence to the contrary.
  • The null hypothesis is accepted as true only if there is convincing evidence for it.

25. What term describes the probability of rejecting the null hypothesis when it is true?

  • Statistical significance
  • Alternative hypothesis
  • P-value
  • Significance level

26. What is the third step when conducting a hypothesis test?

  • Reject of fail to reject the null hypothesis
  • Find the p-value
  • Choose a confidence level
  • Choose a significance level

27. A data professional conducts a hypothesis test. They choose a significance level of 10%. They calculate a p-value of 12.4%. What conclusion should they draw?

  • Reject the alternative hypothesis.
  • Fail to reject the null hypothesis.
  • Fail to reject the alternative hypothesis.
  • Reject the null hypothesis

28. A data professional conducts a hypothesis test. They choose a significance level of 1%. They calculate a p-value of 0.01%. What conclusion should they draw?

  • Reject the alternative hypothesis.
  • Fail to reject the alternative hypothesis.
  • Fail to reject the null hypothesis.
  • Reject the null hypothesis.

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