Final Exam Flashcards
null hypothesis (H0)
statement that is the skeptical viewpoint of your research question
- no difference
4 steps of a hypothesis tests
- define null and alternative hypothesis
- establish null distribution
- conduct statistical test
- draw scientific conculsions
null distribution
sampling distribution we expect from sampling a statistical population when the null hypothesis is trues
alternative hypothesis (HA)
statement that is the positive viewpoint viewpoint of your research question
- everything not in null (mutually exclusive)
- there is a difference
3 factors to the hypotheses
- mutually exclusive
- they describe all possible outcomes = exhaustive
- null always includes the equality statement
non-directional hypothesis
state that there should be a difference in alternative hypothesis
directional hypothesis
state that the difference should be in a specific direction (smaller vs. larger)
statistical inference
conclusion that a set of data are unlikely to come from the null hypothesis
statistical decision
whether we believe our data came from the null distribution or not
- if its likely data came from null distribution = “fail to reject”
- if it is unlikely data came from null distribution = “reject null”
2 probabilities for null distribution
- type 1 error rate
- p-value
type 1 error rate (alpha)
probability of rejecting the null hypothesis when it is true
- set by researcher without any inference to data
p-value (p)
probability of seeing your data, or something more extreme, under the null hypothesis
- are under curve from data to more extreme values
rules of making statistical decision
- if p-value is less than type 1 error rate, then we “reject null hypothesis”
- if p-value is greater than or equal to type 1 error rate, then we “fail to reject null hypothesis”
what the scientific conclusions consider
- strength of inference: how strong evidence is
- effect size: only consider it when we reject null hypothesis (small = low impact)
error rates
probability of making a mistakes
- type I and II have an inverse relationship (when one increases the other decreases)
type II error rates
probability of failing to reject null hypothesis when it is false
- area under alternative distribution from data point to something more extreme
types of t-tests
- single-sample t-tests
- paired-sample t-tests
- two-sample t-tests
single-sample t-tests
evaluate whether mean of your sample is different from some reference value
ex. is mean test score from a sample of high school students different than national standards
paired-sample t-tests
evaluate whether mean of paired data is different from some reference value
- looks at changes in a SU
ex. does tutoring improve grade for a student
two-sample t-tests
evaluate whether mean of two groups are difference from each other (compare two groups)
ex. do dogs sleep more than cats
mean
= m
reference value
= mew - u
- it is given
the reporting of a single-sample t-test should include…
- sample mean and standard deviation
- observed t-score
- degrees of freedom
- p-value
observed t-score
calculated using sample mean, standard deviation, size and reference value