In hypothesis testing, the common level of significance is α = 0.05. Some might argue for a level of significance greater than 0.05. Suppose that web designers tested the proportion of potential web page visitors with a preference for a new web deign over the existing web design. The null hypothesis was that the population of web page visitors preferring the new design was 0.50, and alternative hypothesis was that it was not equal to 0.50. The P -value for the test was 0.20. a. State, In statistical terms, the null and alternative hypotheses for this example. b. Explain the risks associated with Type I and Type II error in this case. c. What would be the consequence if you rejected the null hypothesis for a p -value of 0.20? d. What might be an argument for raising the value of α ? e. What would you do in this situation? f. What is you answer in (e) if the p -value equals 0.12? What if it equals 0.06?
In hypothesis testing, the common level of significance is α = 0.05. Some might argue for a level of significance greater than 0.05. Suppose that web designers tested the proportion of potential web page visitors with a preference for a new web deign over the existing web design. The null hypothesis was that the population of web page visitors preferring the new design was 0.50, and alternative hypothesis was that it was not equal to 0.50. The P -value for the test was 0.20. a. State, In statistical terms, the null and alternative hypotheses for this example. b. Explain the risks associated with Type I and Type II error in this case. c. What would be the consequence if you rejected the null hypothesis for a p -value of 0.20? d. What might be an argument for raising the value of α ? e. What would you do in this situation? f. What is you answer in (e) if the p -value equals 0.12? What if it equals 0.06?
In hypothesis testing, the common level of significance is
α
=
0.05.
Some might argue for a level of significance greater than 0.05. Suppose that web designers tested the proportion of potential web page visitors with a preference for a new web deign over the existing web design. The null hypothesis was that the population of web page visitors preferring the new design was 0.50, and alternative hypothesis was that it was not equal to 0.50. The P-value for the test was 0.20.
a. State, In statistical terms, the null and alternative hypotheses for this example.
b. Explain the risks associated with Type I and Type II error in this case.
c. What would be the consequence if you rejected the null hypothesis for a p-value of 0.20?
d. What might be an argument for raising the value of
α
?
e. What would you do in this situation?
f. What is you answer in (e) if the p-value equals 0.12? What if it equals 0.06?
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.
Hypothesis Testing - Solving Problems With Proportions; Author: The Organic Chemistry Tutor;https://www.youtube.com/watch?v=76VruarGn2Q;License: Standard YouTube License, CC-BY
Hypothesis Testing and Confidence Intervals (FRM Part 1 – Book 2 – Chapter 5); Author: Analystprep;https://www.youtube.com/watch?v=vth3yZIUlGQ;License: Standard YouTube License, CC-BY