Stats terminology and tests

Question 1

What must be disproved in order to accept the alternate hypothesis?

Answer 1

the null hypothesis

Question 2

General example of null hypothesis?

Answer 2

x has no effect on y

Question 3

General example of an alternate hypothesis?

Answer 3

x does have an effect on y

Question 4

When are two samples said to be significantly different?

Answer 4

when p<0.05

Question 5

What is the p value generated from a t test?

Answer 5

the probability that two samples have come from the same population by chance

Question 6

What type error is shown in the p value?

Answer 6

The odds of rejecting the null when the null is true

Question 7

What is a type 1 error?

Answer 7

Rejecting H0 when it is true

Question 8

What do you conclude under a type 1 error?

Answer 8

That a difference exists when one does not exist

Question 9

What is a type 2 error?

Answer 9

Accepting H0 when it is actually false

Question 10

What do you conclude under a type 2 error?

Answer 10

No difference when one does exist

Question 11

What advantages do parametric tests have over non-parametric tests?

Answer 11

More resilient to violations of assumptions and are more powerful

Question 12

What is skew in data?

Answer 12

When the apex of the curve is to the left or the right

Question 13

Positive skew?

Answer 13

Apex of curve is to the left

Question 14

Negative skew?

Answer 14

Apex of the curve is to the right

Question 15

Zero skew?

Answer 15

Apex of curve is in the middle

Question 16

What is kurtosis?

Answer 16

The size and height of the curve

Question 17

Platykotic?

Answer 17

Curve is wider (drops off later)

Question 18

Mesokurtic?

Answer 18

Normal distribution, no unusual width of curve or height

Question 19

What is leptokurtic?

Answer 19

Curve is a lot thinner and apex is higher

Question 20

What is the null hypothesis for tests of normality?

Answer 20

That the distribution is normal

Question 21

Tests for normality?

Answer 21

Shapiro-wilk, Kolmogorov-smirnov, Anderson-darling

Question 22

How can you convert non-normal data into normal data?

Answer 22

By transforming it

Question 23

Examples of a possible transformation?

Answer 23

Log transformation, square root, arcsine

Question 24

What are log transformations used for?

Answer 24

positively skewed data

Question 25

What are square root transformations used for?

Answer 25

Data that follows a poisson distribution

Question 26

What are arcsine transformations used for?

Answer 26

Data using proportions or
percentage

Question 27

What does a t test compare

Answer 27

the means of two samples

Question 28

What does a t test estimate?

Answer 28

the probability that the observed means have come from the same population by chance

Question 29

What are the 3 types of t test?

Answer 29

One sample, independent, and paired

Question 30

What assumptions are used when doing a t test?

Answer 30

Normally distributed data

Question 31

One sample t test null hypothesis?

Answer 31

The mean of a sample group is not significantly different from the overall mean

Question 32

One sample t test alternate hypothesis?

Answer 32

The mean of a sample group is significantly different from the overall mean

Question 33

Question that you would try to answer with a one sample t test?

Answer 33

Does the observed mean of x sample differ enough from the mean of y population to suggest that there may be something causing it, or could it have occurred by chance

Question 34

When do you do a two tailed t test?

Answer 34

When you don’t have an idea of the direction of the difference. (e.g. you have no idea what effect z variable will have on x sample to make it different from y mean)

Question 35

When do you do a one tailed t test?

Answer 35

When you do have an idea of the direction of the difference (e.g. you think that z variable will have w effect (making it higher or lower) on x sample to make it different from y mean)

Question 36

Paired t test null hypothesis?

Answer 36

the true mean difference between the paired samples is zero (i.g. there isn’t any difference between the values before and after the variable has been applied)

Question 37

If the null hypothesis in a paired t test was true, what would all observable explained differences be explained by?

Answer 37

random variation

Question 38

Paired t test alternate hypothesis?

Answer 38

The true mean difference between the paired samples is not equal to zero (there is a difference between the values before and after the variable has been applied)

Question 39

If the null hypothesis in a paired t test was rejected what could the observable differences be explained by?

Answer 39

The variable that has affected them (e.g. conditions grown in, training done etc)