Definitions

Question 1

Expectation E(x) and variance Var(x) for N(mu, sigma)

Answer 1

E(x) = mu
Var(x) = sigma

Question 2

Expectation E(x) and variance Var(x) for N(mu, sigma)

Answer 2

E(x) = mu
Var(x) = sigma

Question 3

Expectation E(x) and variance Var(x) for N(mu, sigma)

Answer 3

E(x) = mu
Var(x) = sigma

Question 4

Expectation E(x) and variance Var(x) for N(mu, sigma)

Answer 4

E(x) = mu
Var(x) = sigma

Question 5

Expectation E(x) and variance Var(x) for N(mu, sigma)

Answer 5

E(x) = mu
Var(x) = sigma

Question 6

Sample

Answer 6

Set of values (randomly (assumption)) selected from a population

Question 7

Mean

Answer 7

Average value of a set of values

Question 8

Median

Answer 8

The value in the middle of your set of sorted data
For odd numbered set this is the middle value
For even numbered sets this is the average of two middle values

Question 9

Variance

Answer 9

This is how much the values in the set deviate from their mean.
Calculated through the sum of all values in your set subtracted by the mean, square this to eliminate negative values and divide the outcome by n-1, where n is the size of your set

Question 10

Standard deviation

Answer 10

The square root of the variance, which was squared to eliminate the negative values.

Question 11

Which numerical summaries are location and which are scale?

Answer 11

Location: mean and median
Scale: variance and standard deviation

Question 12

Histogram

Answer 12

A barplot of a set X where the AREA of the bar over a cell (called a bin, see it as a little interval) is equal to the number of observations in that cell divided by the size of X.
The sum of bars is therefore equal to 1 (100%)

Question 13

Correlation

Answer 13

The correlation between two variables quantifies the linear relation between them.
It is calculated by taken the sum of the product of the subtraction of the mean of all the variables in both sets, and dividing it by the square root of the product of both set’s variances.

Question 14

Correlation values and corresponding relations between the two sets

Answer 14

+1: perfect LINEAR relation with positive slope

• 1: perfect LINEAR relation with negative slope
  0: No linear relation

Question 15

Normal QQ-plot

Answer 15

A plot that matches the quantiles of two sets, to see whether it is normally distributed

Question 16

Boxplot

Answer 16

Display the different quantile values, range and median of a data set

Question 17

Sample mean distribution

Answer 17

The distribution of the mean of a sample
The reason it is a distribution, is because every sample is different and thus every mean as well.
For x~N(mu,sd), sample mean distribution is x^bar~N(mu,sd/n) where n is the size of x^bar

Question 18

Standardizing the mean and back

Answer 18

z=(X-u)/sd

x=u+sd*z

Question 19

Point estimate of a parameter

Answer 19

A point estimate of any parameter is a function of only the observed data

Question 20

Confidence interval alpha of a parameter

Answer 20

The chance of 1-alpha that the defined interval contains the true value of the parameter

Question 21

T-distribution

Answer 21

Used for a sample standard deviation, because it is not known whether it is normally distributed