# Statistics 210 Exam 2

## 94 terms

### probability

equal to the number of outcomes classified as A divided by the total number of possible outcomes

### chance

probability is likelihood that result occurred by ______

### random sampling

each individual in the population has an equal chance of being selected

### sampling with replacement

each individual in the sample is returned to the population before another sample is drawn, keeps probabilities constant

### random sampling, sampling with replacement

Two important assumptions of probability

### 68-95-99.7%

Normal distributions use _______ rule

### standard normal table

Uses z scores to determine probability

### low probability region

corresponds to a relatively small proportion of the distribution, usually 0.05 or less

### high probability region

corresponds to a relatively large proportion of the distribution, usually 0.95 or more

### 1.96

critical point for high and low probability is a z score of +/-

### statistic

describes a characteristic of the sample, such as the mean of the sample scores

### parameter

describes a characteristic of the population, such as the mean of all population scores

### sampling error

the difference between the sample statistic and the population parameter

### inferential statistics

techniques used to make generalizations about the population from which the sample was drawn, to determine the likelihood that the sample result is due to chance/error

### result is due to chance, result is real

two possible interpretations of result

### hypothesis testing

method of using sample data to evaluate a claim about a population parameter, a method for making rational decisions about the reality of out sample results

### rational

systematic and logical with a relatively high likelihood of being correct

### null hypothesis

there is no effect, no relationship, no difference, nothing real in the population, IV does not affect DV, parameter = 0

### alternative hypothesis

there is an effect, relationship, difference, something is happening, IV affects DV, parameter ≠ 0

### fail to reject null hypothesis

if p is greater than alpha then we

### rho

used when testing correlation/relationship between two variables in a population

### mu

used when testing difference between mean of 2 groups in population

### state the null and alternative hypotheses

step 1 of hypothesis testing

### words, parameter notation

state null and alternative hypotheses in _______ and in ______

### set alpha

step 2 of hypothesis testing

### collect data, compute statistic

step 3 of hypothesis testing

### determine probability

step 4 of hypothesis testing

step 5 of hypothesis testing

### reject null

if probability less than alpha

### fail to reject null

if probability is greater than alpha

### statistically significant

findings are said to be _______ when there is a low probability of the results occurring by chance alone, , does not indicate anything about magnitude of effect or relationship

### errors

_______ in hypothesis testing are possible because decisions are based on probability, it is possible that our conclusions are incorrect

### type 1 error

incorrect rejection of the null hypothesis, concluding there is an effect when in reality there is no effect, false positive

type 1 error =

### type 2 error

incorrect acceptance of null hypothesis, concluding there is no effect when in reality there is a real effect, false negative

### probability of replication

the probability that an effect will be seen again if the study is repeated

### power

the likelihood of getting a statistically significant result, function of sample size and effect size

### effect size

strength of relationship between two variables

### sampling distributions

used to determine probability

### sampling distribution

theoretical distribution that shows the frequency of each possible value of the statistic from sample size n when the null hypothesis is true

### expected value

mean of sample means = population mean

### sampling error

for a single sample, the difference between the sample statistic and the population parameter

### standard error

across multiple samples, average difference between sample statistic and population parameter, standard deviation of sampling distribution, as n increase error decreases

### standard error of the mean

average distance of the sample means from the population mean

### central limit theorem

as n gets larger, the sampling distribution of sample means will approach a normal distribution

### critical value

value of the statistic that has probability equaling alpha, value of the statistics that is at the boundary of the critical region

### critical region

area of distribution that is beyond the critical value, contains values that have a probability less than or equal to alpha

### two tailed probability

used when hypotheses are nondirectional, critical region in both tails

### one tailed probability

used when hypotheses are directional, critical region in one tail

### frequency

Sampling distribution of r shows the ______ of each possible value of r

### probability

For any given sample value of r, we can use the sampling distribution of r to determine the _______ that is occurs by chance

### pearson value table

use to determine critical values of r

### probability

can use critical values of r to calculate _______

### estimation

inferential technique of using sample statistics to estimate a population parameter

### point estimate

a single value from the sample is used to estimate the population parameter, varies from sample to sample due to sampling error

### interval estimate

range of values used to estimate the population parameter, sample % +/- margin of error

### confidence interval

a range of values that has a specific probability of containing the value of the population parameter

### confidence interval of the mean

a range that is expected to contain the value of the population mean

### confidence

the probability that the interval contains the true value of the parameter

### 1.96

rage of values with 95% probability of containing population value use z score of

### 2.58

rage of values with 99% probability of containing population value use z score of

### sample statistic +/- margin of error

confidence interval for a population parameter equals

### z score times s/sqN

margin error equation

### increases

As confidence level increases, confidence width

### decreases

As sample size increases, confidence width

### increases

As standard deviation increases, confidence width

### true value

% confident that the specified interval contains the ______ of the population parameter

### not statistically significant

if the confidence interval of the mean difference includes the value of 0 then we conclude that the mean difference is

### no correlation

if the CI of r includes the value of 0 then we conclude there is

### significant difference

if confidence intervals of each group do not overlap then we can conclude there is a

### need a t test

if confidence intervals overlap then

### t test

used when the DV is continuous and the sample result consists of one or two means

### t

a statistic that measures the mean difference in standard deviation units

### one sample t test

used to determine if a single sample mean is different from a known population mean

### related samples t test

paired samples, two groups are connected in some way that the two group means are related

### repeated measures

one group of participants is measured twice, such as before and after treatment, within subjects design

### matched subjects

there are two groups of participants, and each participant in one group is paired with a subject in the other group

### independent samples t test

used to determine if means from 2 unrelated groups are significantly different, between subjects design

### separation

T indicates ______ between groups

### larger

greater the separation the _____ the t

### M1-M2/SE

Independent samples t test equation

### Md/SE

related samples t test equation

### probability

use sampling distribution of t to determine the ______ of an obtained value of t

### normality

scores are normally distributed in each of the populations from which samples are taken

### independence of observations

each score in the group does not affect and is not affected by any other score in the group

### homogeneity of variance

assumption applies to independent samples t test only, populations from which the samples are taken have equal variability

### robust

not affected much by violations of assumptions

### proportion of variance, cohens d

two approaches when you have significant t test result

### t2/t2+df

proportion of variance explained equation for t test

### cohens d

measure of effect size that assesses the difference between two means in terms of standard deviation

### 0.2

d = _____ 85% overlap, small effect size

### 0.5

d = _____ 67% overlap, medium effect size

### 0.8

d = _____ 53% overlap, large effect size

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