CK020 - Probability & Statistics

Question 1

What is the ‘Cumulative Distribution Function’ ?

Answer 1

The probability that a random variable X takes a value less/equal to x

Question 2

What is the ‘Probability Density Function’ ?

Answer 2

The Probability that a continuous random variable X takes a value in interval [a, b]

Question 3

How are the CDF and PDF related?

Answer 3

• PDF is the derivative of the CDF
• CDF is the integral of the PDF

Question 4

What is the ‘variance’ ?

Answer 4

Measures how far the values of a random variable X are spread out from the mean

Question 5

What is the ‘covariance’ ?

Answer 5

Measure of how much 2 random variables change together

Question 6

What is a ‘correlation’ ?

Answer 6

Standardized version of the covariance, and is a measure of linear dependence of 2 random variables

Question 7

What is the ‘estimand’ ?

Answer 7

Parameter of the target population we wish to estimate from a sample

Question 8

What is the ‘standard error’ ?

Answer 8

Standard deviation of the results from all possible samples

Question 9

What is the interpretation of a ‘95% CI’ ?

Answer 9

If we had 100 samples with their own 95% CI, we expect 95 of them to contain the ‘true parameter value’

Question 10

What is the interpretation of a ‘p-value’ ?

Answer 10

The probability to obtain a value for a test statistic at least as extreme as in the original sample under the assumption that the null hypothesis is correct

Question 11

What is a ‘type 1 error’ ?

Answer 11

Falsely rejecting the H0 (So the H0 is actually true, but we reject it)

Question 12

What is a ‘type 2 error’ ?

Answer 12

Falsely NOT rejecting H0 (So the H0 is actually NOT true, but we do NOT reject it)

Question 13

What is ‘sampling variability’ ?

Answer 13

Variability that stems from the fact that our study is only one of the possible samples from the target population