hypothesis testing (w6)

Question 1

what do you change this to: Test whether a scientific hypothesis is supported by the evidence (i.e. data) provided”

Answer 1

prefer to discuss based on probability:
Calculate the probability of obtaining the observed data if the hypothesis is true

Question 2

what are p-values

Answer 2

probabilities used to reject hypotheses, probability that your hypothesis is right

Question 3

what is a threshold level for the p-value called and when does it need to be defined

Answer 3

alpha-level, prior to analysis

Question 4

if threshold for p value is 0.05, when would you accept or reject hypothesis

Answer 4

p-value < 0.05 , reject hypothesis
p-value > 0.05 , accept hypothesis

Question 5

what is a null hypothesis

Answer 5

a hypothesis against the research question, claiming there is no difference in result and the only differences observed are just noise/error

Question 6

what is a research/alternative hypothesis

Answer 6

the opposite to the null hypothesis claiming that there is a different in the result

Question 7

example of null and alternative/research hypothesis with vaccine effect on infective rate

Answer 7

null: vaccine has no effect on infection rate
r/alt: vaccine has an effect on infection rate

Question 8

how do you test the null hypothesis in research

Answer 8

test the probability that null hypothesis is true (ie there is no effect/relationship)

Question 9

why do you test null not research hypothesis

Answer 9

you can’t prove something is true, but you can prove something is false

Question 10

how to reject null hypothesis

Answer 10

firstly define it - there is no significant difference, then show that there is a statistically significant difference

Question 11

when testing null, how do you get the significancy

Answer 11

significancy estimated by the probability that the difference occurred by changes, called p-value

Question 12

what is the threshold for significancy usually

Answer 12

p < 0.05

Question 13

what are 2 types of error

Answer 13

type 1 : false-positive
type 2 : false-negative

Question 14

what is type 1 error

Answer 14

false positive: reject null when its true

Question 15

what is type 2 error

Answer 15

false negative: not to reject null when its false

Question 16

what is a binomial test

Answer 16

statistical test that concerns whether a proportion observed in data is different from a known proportion

Question 17

when do you reject null

Answer 17

when p-value is below alpha level

Question 18

what are three types of binomial test

Answer 18

cumulative probability from 0 to observed
1-cumulative probability from observed to max
two-tailed cumulative probability same distance from mean

Question 19

which binomial test would you use for observed proportion < expected proportion

Answer 19

Cumulative probability from 0 to observed

Question 20

which binomial test would you use for observed proportion > expected proportion

Answer 20

1 – cumulative probability from observed to max

Question 21

which binomial test would you use for observed proportion not equal to expected proportion

Answer 21

Two-tailed cumulative probability same distance from the mean

Question 22

how to conduct binomial test

Answer 22

describe null with expected proportion, report observed proportion from data, report p-value that null is true, report confidence interval (CI)

Question 23

what is a confidence interval

Answer 23

a range of plausible values associated with a confidence level, usually 95%

Question 24

what does confidence interval mean in binomial test

Answer 24

means you are 95% certain that the true proportion falls within the CI