(1) Basic Statistical Concepts

Question 1

Normalization

Answer 1

forces something into a normal distribution

Question 2

Standardization

Answer 2

dividing it by something to remove its effect

Ex: dividing something by area of pop size

Question 3

QQ/quantile plot

Answer 3

Visualization to see if data is normally distributed

negative = points curve beneath line
positive skew = points curve above
normal = points are on line

Question 4

r or coefficient of correlation

Answer 4

looks at whether 2 variables vary together

Question 5

Range for correlation coefficient and what is positive/negative/0?

Answer 5

-1 to 1
positive = both variables go up
negative = one goes up, one goes down
0 = no association

Question 6

Standard deviation

Answer 6

measures how far data values are from the mean
little variation in values means small standard deviation

Question 7

Analysis of variance (ANOVA)

Answer 7

Parametric test to see if there are significant differences in 3+ categorical groups

Question 8

Covariance

Answer 8

Testing 2 variables to see if they vary together or not using a correlation coefficient (r)

Question 9

Kernel density (3 facts about it)

Answer 9

1. removes statistical noise from data by smoothing it
2. Uses Gaussian weighting (closer points = more weight)
3. good for showing generalized densities of points

Question 10

p value (3 facts)

Answer 10

1. doesn’t tell you size of difference, just that there is one
2. says if result is significant
3. whether or not to reject null hypothesis

Question 11

How to use a p value in a sentence to explain random chance and null hypothesis (hint: %)

Answer 11

1. ___% chance you saw these results by random chance
2. ___% chance you are falsely rejecting the null hypothesis

Question 12

histogram

Answer 12

x-axis = category
y-axis = frequency in that category

way to visualize frequency/distribution of data

Question 13

Z score meaning

Answer 13

Number of standard deviations away from the mean

Question 14

Z score formula

Answer 14

(score - mean) / standard deviation

Question 15

Coefficient of determination (r-squared)

Answer 15

High = good fit
Low = poor fit
How much of the variance in y is described by variance in x

Question 16

Sentence using coefficient of determination

Answer 16

Variable x explains 80% of the variation in variable y

Question 17

Kruskall-Wallis test

Answer 17

look at more than 2 populations for similarity

non-parametric version of ANOVA

Question 18

Central limit theorem

Answer 18

Distribution approaches normal as sample size increases

Question 19

Mann-Whitney U

Answer 19

compares 2 sample populations
non-parametric
scores are ranked from small to large and then ranks of scores are compared

Question 20

Sample mean

Answer 20

mean of a sample of the data

Question 21

non-parametric statistics (list tests)

Answer 21

does not follow a Gaussian distribution

Mann Whitney-U, Kruskall Wallis, Spearman’s Rho

Question 22

Normal (Gaussian) distribution (3 facts)

Answer 22

1. follows a bell curve
2. uses parametric stats
3. defined using the mean/standard deviation

Question 23

Normal QQ plot

Answer 23

is like a qq/quantile plot but compares the data quantiles against the quantiles of a normal distribution

Question 24

Null hypothesis

Answer 24

no significant difference, effect, or relationship in the population

Question 25

Parametric statistics (also list tests)

Answer 25

follows a Gaussian distribution 2 sample t test, ANOVA, Pearson's R/correlation

Question 26

Parsimony

Answer 26

Keep it simple and make it clear

Question 27

Pearson's R

Answer 27

measure the strength/direction between 2 variables Parametric

Question 28

Residual plot

Answer 28

plots the residuals from a regression model If there is an obvious pattern to the residuals than the model might not work

Question 29

Residuals

Answer 29

distance between point and the best fit line kind of like error

Question 30

Interpreting residuals (+ and -)

Answer 30

+ = overestimating rates of something - = underestimating rates of something

Question 31

Shapiro test

Answer 31

null hypothesis = samples come from a normal distribution

Question 32

Spearman's Rho

Answer 32

compares differences between the ranks in 2 data sets values range from -1 - +1 (same as r-squared value)

Question 33

Square of the error

Answer 33

quantifies difference between observed and expected values