A political candidate is recruiting volunteers to help with their campaign. On their website they are testing to see if a button that says “Learn More” gets more responses than a button that says “Sign Up” They run both versions of the website for 30 days in a way that users are randomly assigned to a version of the website. After the trial period of the 7845 visitors who visited the “Learn More” version 689 people clicked the button, and of the 7861 people who visited the “Sign Up” version 513 clicked the button. x1=number of successes group 1 689 n1=sample size group 1 7845 x2=number of successes group 1 513 n2=sample size group 1 7861.00 Sample Difference in Proportion (group 1-group 2) 0.02257 Standard Error (se) 0.0042 z test statistic 5.319 p-value (One-Tail) 0.0000 p-value (Two-Tail) 0.0000 From the Given data, What is the point estimate for difference in proportion? (Learn More group minus Sign Up group) 1. 0.0226 2. 0.0156 3. 0.0309 The 90% confidence interval for the difference in proportion of clicks of the "Learn More" group compared to the "Sign Up" group does not contain the value zero. Therefore there is statistically significant evidence that the proportions are different. True or False? Choose the best option in the (parenthesis): When conducting the hypothesis test for the difference in proportion the p-value was (greater/less) than the alpha level of 0.1. Therefore we (reject/fail to reject) the null hypothesis and conclude there (is/is not) statistically significant evidence that the proportion of clicks received is greater when "Learn More" is used rather than "Sign Up" . Given the p-value you found and choice you made concerning the test to see if the proportion who click on the "Learn More" button is greater than the "Sign Up" button what type of error could you have made? Choose the best answer. options: Type I error, I concluded there was a difference when perhaps there was not. Type I error, I did not find evidence of a difference but perhaps there was a difference in proportion. Type II error, I did not find evidence of a difference but perhaps there was a difference in proportion. Type II error, I concluded there was a difference when perhaps there was not.
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
A political candidate is recruiting volunteers to help with their campaign. On their website they are testing to see if a button that says “Learn More” gets more responses than a button that says “Sign Up” They run both versions of the website for 30 days in a way that users are randomly assigned to a version of the website. After the trial period of the 7845 visitors who visited the “Learn More” version 689 people clicked the button, and of the 7861 people who visited the “Sign Up” version 513 clicked the button.
| x1=number of successes group 1 | 689 | |
| n1= |
7845 | |
| x2=number of successes group 1 | 513 | |
| n2=sample size group 1 | 7861.00 | |
| Sample Difference in Proportion (group 1-group 2) | 0.02257 | |
| Standard Error (se) | 0.0042 | |
| z test statistic | 5.319 | |
| p-value (One-Tail) | 0.0000 | |
| p-value (Two-Tail) | 0.0000 | |
From the Given data, What is the point estimate for difference in proportion? (Learn More group minus Sign Up group)
| 1. |
0.0226 |
| 2. |
0.0156 |
| 3. |
0.0309 |
The 90% confidence interval for the difference in proportion of clicks of the "Learn More" group compared to the "Sign Up" group does not contain the value zero. Therefore there is statistically significant evidence that the proportions are different.
True or False?
Choose the best option in the (parenthesis):
When conducting the hypothesis test for the difference in proportion the p-value was (greater/less) than the alpha level of 0.1. Therefore we (reject/fail to reject) the null hypothesis and conclude there (is/is not) statistically significant evidence that the proportion of clicks received is greater when "Learn More" is used rather than "Sign Up" .
Given the p-value you found and choice you made concerning the test to see if the proportion who click on the "Learn More" button is greater than the "Sign Up" button what type of error could you have made? Choose the best answer.
options:
|
|
Type I error, I concluded there was a difference when perhaps there was not. |
|
|
Type I error, I did not find evidence of a difference but perhaps there was a difference in proportion. |
|
|
Type II error, I did not find evidence of a difference but perhaps there was a difference in proportion. |
|
|
Type II error, I concluded there was a difference when perhaps there was not. |
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