Lecture 7

Question 1

measures of location

Answer 1

mean, median, quartile

Question 2

measures of spread

Answer 2

range (max-min), interquartile range, variance, standard deviation

Question 3

define hypothesis

Answer 3

A statistical hypothesis is a statement of belief about population parameters.

Question 4

null hypothesis

Answer 4

• The null hypothesis, symbolized by H0, is a statement claiming that there is no difference between the assumed or hypothesized value and the population
parameter; null means “no difference.”

Question 5

alternative hypothesis

Answer 5

• The alternative hypothesis, which we symbolize by H1 (some textbooks use HA) is a statement that disagrees with the null hypothesis.

Question 6

two tailed test?

Answer 6

A two-tailed test is a statistical test in which the critical area of a distribution is two-sided and tests whether a sample is greater than or less than a certain range of values. If the sample being tested falls into either of the critical areas, the alternative hypothesis is accepted instead of the null hypothesis.

Question 7

one tailed test?

Answer 7

A one-tailed test is a statistical test in which the critical area of a distribution is one-sided so that it is either greater than or less than a certain value, but not both. If the sample being tested falls into the one-sided critical area, the alternative hypothesis will be accepted instead of the null hypothesis

Question 8

p-value?

Answer 8

A p-value is the probability of getting the outcome observed (or one more extreme), assuming null hypothesis to be true

Question 9

type 1 error?

Answer 9

We denote the probability of making type I error as α. Significance level. Typically in biology/medicine equals 0.05 (except omics and pharmacy).

Question 10

type 2 error?

Answer 10

• We denote the probability of making type II error as β. The test correctly rejects the null hypothesis with probability 1 − β, the latter we define as the power of the test. Typically between 0.8 and 0.95.

Question 11

If p < 0.05, then we

Answer 11

reject null hypothesis

Question 12

If p ≥α, we..

Answer 12

accept null hypothesis

Question 13

how we form conclusion, when we reject null hypothesis?

Answer 13

difference is statistically significantly different

Question 14

how we form conclusion, when we accept null hypothesis?

Answer 14

There is no evidence to reject H0, because … no statistically significant difference…

Question 15

which is the strongest normality test?

Answer 15

Shapiro-Wilk

Question 16

what is the objective of t test?

Answer 16

to compare the means of the population

Question 17

what we should do before applying t-test?

Answer 17

test for normality

Question 18

when we reject null hypothesis?

Answer 18

when p-value is smaller than 0.05

Question 19

when can we use ANOVA?

Answer 19

to compare the mean differences between any number of groups or treatments

Question 20

what is anova test?

Answer 20

An ANOVA test is a way to find out if survey or experiment results are significant. In other words, they help you to figure out if you need to reject the null hypothesis or accept the alternate hypothesis. Basically, you’re testing groups to see if there’s a difference between them

Question 21

what is dependent variable?

Answer 21

Y (variable whose averages are compared) is metric, normally distributed.

Question 22

factor variable

Answer 22

categorical. Due to it we know the group to which the respondent belongs.

Question 23

when we use one way anova?

Answer 23

used when you want to test two groups to see if there’s a difference between them

Question 24

when we use two way anova?

Answer 24

used when you have one group and you’re double-testing that same group. For example, you’re testing one set of individuals before and after they take a medication to see if it works or not.