Hypothesis testing

Question 1

What are parametric data?

Answer 1

data that are normally distrubuted

Question 2

What are 3 types of hypotheses you can test?

Answer 2

1. Single sample (comparing a sample to a known value e.g. average weight of woman in USA)
2. two independent samples (comparing two experimental conditions and different participants were assigned to each condition)
   - two groups of subjects in two different conditions (experimental and control)
3. two dependent samples (two experimental conditions and the same participants took part in both conditions of the experiment)
   - same group of subjects in the conditions

Question 3

What is the null hypothesis?

Answer 3

he position that any difference is simply due to sampling error (chance variation)

Question 4

What is the alternate hypothesis?

Answer 4

the position that any difference is not due to sampling error but rather due to the effect of the experimental manipulation

Question 5

What are the 8 steps of hypothesis testing?

Answer 5

1. choose a hypothesis to test
2. choose an alternate hypothesis
3. choose a significance level
4. determine the distribution
5. determine the critical region
6. establish a rejection rule
7. calculate the statistic
8. draw the appropriate conclusion

Question 6

What is alpha

Answer 6

he probability of making a Type I error

Question 7

what is beta

Answer 7

the probability of making a Type II error

Question 8

what is power

Answer 8

the probability of correctly rejecting the null hypothesis when the null hypothesis is false (i.e. the probability of NOT making a type 2 error)

Probability that a given test will find an effect assuming that one exists in the population

Question 9

what is a type 2 error

Answer 9

Incorrectly failing to reject the null hypothesis when the null hypothesis is false

Question 10

what is a type 2 error

Answer 10

Incorrectly failing to reject the null hypothesis when the null hypothesis is false

Question 11

What factors influence alpha?

Answer 11

the researcher (based on the consequences of committing a type 1 error)

Question 12

What are the factors that affect beta? (6)

Answer 12

1. alpha
2. the alternative hypothesis
3. the size of the samples (large sample = more power)
4. the real difference between the two means (the magnitude of the true difference i.e. effect size)
5. parametric vs non-parametric tests (parametric have more power)
6. independent- vs dependent-groups designs

Question 13

how do you calculate the probability of rejecting the null hypothesis? (power)

Answer 13

Need to base this on comparing 2 distributions

- the distribution you would get if the null hypothesis was true vs if the null is false

Question 14

How does independent- vs dependent-groups designs impact power?

Answer 14

By impacting amount of variability

-> dependent group designs have fewer sources of variability and therefor more power to detect a treatment effect

Question 15

What are the sources of variability in an dependent groups (within groups) t test?

Answer 15

1. Experimental error

2. Treatment effect

Question 16

What are the sources of variability in an independent groups (between groups) t test?

Answer 16

1. Experimental error
2. Individual differences
3. Treatment effect

Question 17

What is experimental error

Answer 17

1. fluctuations in external conditions (e.g. room temperature, lighting)
2. temporary variations in the subjects themselves (e.g. distracted, tired)

Question 18

What are individual differences

Answer 18

Stable differences between individuals (e.g. intelligence, personality factors)