hypothesis testing

Question 1

how do you do a binominal test for hypothesis testing?

Answer 1

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

Question 2

what can a statical test systematically test?

Answer 2

• tests whether a given scientific claim is valid or not

Question 3

what are answers like in most cases in scientific research?

Answer 3

• no definitive answers to any kind of questions so scientists prefer to discuss based on probability

Question 4

when do we reject the hypothesis?

Answer 4

• if the probability is very low

Question 5

when do we accept the hypothesis?

Answer 5

• if the probability is not so low

Question 6

what are p -values?

Answer 6

• probabilities used to reject hypotheses

Question 7

what are the threshold levels for p- values? when are they defined?

Answer 7

• alpha level
• normally 0.05
• needs to be defined prior to a study

Question 8

what p - value do you reject the hypothesis at?

Answer 8

• if p- value < 0.05

Question 9

what p -value do you accept your hypothesis at?

Answer 9

• if p- value > 0.05

Question 10

what is a null hypothesis?

Answer 10

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

Question 11

what is the symbol for null hypothesis?

Answer 11

H 0

Question 12

what do scientifistic often have to struggle against?

Answer 12

• struggle against the probability that the observed difference could be chance due to noises

Question 13

what is the research/ alternative hypothesis?

Answer 13

• claims that there is a difference in the result

Question 14

what is the symbol for research hypothesis?

Answer 14

H a

Question 15

in statistics what do we test?

Answer 15

• test the probability that the null hypothesis is true

Question 16

why don’t we test the research probability?

Answer 16

• because you can never prove something is true
• can prove the null hypothesis is false

Question 17

what do we do in hypothesis testing?

Answer 17

• first define H0
• make an attempt to reject this by showing there is a statistically significant difference

Question 18

how is significance estimated?

Answer 18

• by the probability that the difference occurred by chance (p- value)

Question 19

what always occurs when dealing with probability?

Answer 19

• errors
• two types; 1 and 2

Question 20

what is type 1 error?

Answer 20

• false positive
• reject the null hypothesis when it is true

Question 21

what is type 2 error?

Answer 21

• false negative
• not to reject the null hypothesis when it is false

Question 22

do we want to minimise one of the types of errors more?

Answer 22

• researchers need to minimise both but based on your research question you may want to focus on one type more than the other

Question 23

what are the three typical types of tests?

Answer 23

• observed proportion< expected proportion
• observed proportion > expected proportion
• observed proportion = expected proportion

Question 24

described observed proportion> expected proportion

Answer 24

• 1 - cumulative probability from observed to max

Question 24

describe observed proportion < expected proportion

Answer 24

- cumulative probability from 0 to observed

Question 25

describe observed proportion = expected proportion

Answer 25

- two tailed cumulative probability same distance from the mean

Question 26

how do you conduct a binominal test in hypothesis testing?

Answer 26

- describe null hypothesis with expected proportion - report observed proportion from data - report probability (p- value) that the null hypothesis is true - optionally report the confidence interval

Question 27

what is the confidence interval?

Answer 27

- range of plausible values associated with a confidence level

Question 28

what is the normal confidence interval and what does this mean?

Answer 28

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

Question 29

what does confidence interval include?

Answer 29

- often used to the range in which true proportion may lie