module 9

Question 1

Statistical Inference

Answer 1

Want to extend implications to the setting where we only have sample data
Want to make a statement about a feature of the population

Question 2

Steps for Hypothesis Testing

Answer 2

1. Identify and define the parameter of interest
2. Define the competing hypotheses to test
3. Set the evidence threshold, formally called the significance level
4. Generate or use theory to specify the sampling distribution and check conditions
5. Calculate the test statistic and p-value
6. Evaluate your results and write a conclusion in the context of the problem.

Question 3

Type I Error

Answer 3

Rejecting a true null hypothesis (false positive).
Significance level measures this

Question 4

Type II error

Answer 4

Failing to reject a false null hypothesis (false negative)
Beta measures this

Question 5

p-value

Answer 5

the probability of getting a test statistic as extreme or more extreme (in the direction of the alternative hypothesis), assuming the null hypothesis is true.

Question 6

confidence intervals

Answer 6

use when we have 2 competing theories that we are trying to choose between

Question 7

Confidence interval steps

Answer 7

1. Identify and define the parameter of interest
2. Determine the confidence level
3. Generate or use theory to specify the sampling distribution and check conditions
4. Calculate the middle region of your sampling distribution, according to your confidence level
5. Write a conclusion in the context of the problem.

Question 8

Confidence level interpretation

Answer 8

“If we gathered repeated random samples of the same size and calculated a CL% confidence interval for each, we would expect CL% of the resulting confidence intervals to contain the true parameter of interest.”
we expect CL% of our intervals to be correct

Question 9

name scenario: 1 categorical

Answer 9

proportion (p)

Question 10

name scenario: 1 quantitative

Answer 10

mean (mu)

Question 11

name scenario: 2 categorical

Answer 11

proportion_1 - proportion_2

Question 12

name scenario: 1 categorical and 1 quantitative

Answer 12

mean_1 - mean_2

Question 13

name scenario: 2 quantitative

Answer 13

simple linear regression

Question 14

name scenario: 3 categorical

Answer 14

multiple logistic regression

Question 15

name scenario: 3 quantitative

Answer 15

multiple linear regression

Question 16

confidence interval interpretation

Answer 16

“We are CL% confident that are true parameter of interest lies in (a,b).”

Question 17

describe distribution of simulated sampling distribution

Answer 17

Shape
Outliers
Center
Spread

Question 18

p-value interpretation

Answer 18

The p-value represents the probability of observing a sample as extreme as the one calculated (or more extreme), assuming the null hypothesis is true.