Reference no: EM133201465

Question 1:

A hospital ER manager has been monitoring the admissions to her clinic over the course of a week. The data she collected is found in the clinic.csv file in your data folder. There were 600 admissions to the ER that week.

The previous year she calculated the average percentage of admissions in the four time blocks: - Morning 15% - Afternoon 30% - Evening 35% - Night 20%

Is there sufficient evidence in the recent data to indicate the proportions have changed?

Question 2:

A promoter has gotten a state to consider legalizing online betting. The state took an opinion poll and the data is found in the gambling.cvs file in your data folder.

Is there a difference between poll participants who are and are not gamblers on whether gambling should be online or not online?

Follow the Downey's Infer process steps to answer the questions fully.

These are the generalized steps. You will need most/all depending upon how you choose to answer the question.

• Step 1: Calculate a sample statistic, or "delta," δ. This is the main measure you care about: the difference in means, the average, the median, the proportion, the difference in proportions, etc.
• Step 2: Use simulation to invent a world where δ is null. Simulate what the world would look like if there was no difference between two groups, or if there was no difference in proportions, or where the average value is a specific number.
• Step 3: Look at δ in the null world. Put the sample statistic delta in the null world and see if it fits well.
• Step 4: Calculate the probability that δ could exist in null world. This is the p-value, or the probability that you'd see a δ at least that high in a world where there's no difference.
• Step 5: Decide if δ is statistically significant. Choose some evidentiary standard or threshold for deciding if there's sufficient proof for rejecting the null world. Standard thresholds (from least to most rigorous) are 0.1, 0.05, and 0.01.