Congratulations! You now know how to use a sample size calculator to figure out an appropriate sample size for an A/B Test! As a reminder, you learned about the following inputs to a sample-size calculator:

- Baseline Conversion Rate
- Minimum Detectable Effect
- Significance Threshold

### Instructions

As a final exercise, let’s put everything together into a single calculation. Suppose that you are running a business and want to see if a new advertisement will drive more clicks on your website. Currently, about 10% of people who see your ad are clicking on it. You want to run the new ad if at least 14% of people will click the new ad. When you run your Chi-Square test after collecting your data, you plan to use a significance threshold of 0.05, so that your chances of a false positive are relatively low. Try the following:

- Based on the description above, identify the baseline conversion rate and significance threshold
- Based on the description above, calculate the minimum detectable effect (hint: it’s not 4%!)
- Plug in your baseline, minimum detectable effect, and significance threshold to the provided calculator
- Calculate the total sample size needed for this experiment (note: this calculator assumes that exactly half of the sample will see each version of the ad)

The solution to this problem is located in **solution.py** if you’d like to check your work.