Chapter 15 B

Question 1

Goal of inferential statistics

Answer 1

to use samples as basis for reaching general conclusion about the POPULATION from which the samples were collected

Question 2

What stands in the way of inferential statistics’ goal?

Answer 2

sampling error

Question 3

what is sampling error?

Answer 3

error due to discrepancy between the info available from a sample to the true situation that exists in the population. A NATURALLY EXISTING difference between a sample statistic and the coinciding population parameter.

A sample does not portray a perfectly accurate picture of the population

Question 4

What is a hypothesis test?

Answer 4

a systematic and statistical procedure that determines whether the sample data provides convincing evidence to support the original research hypothesis. Ensures that the difference in sample means is CAUSED BY TREATMENT and NOT BY CHANCE

Question 5

Hypothesis tests help ensure ____ validity

Answer 5

internal validity

Question 6

Goal of a hypothesis

Answer 6

to make statements about a population using only data collected from a sample, and to rule out chance as a threat to internal validity or plausible explanation for treatment results.

Question 7

5 basic elements of a hypothesis

Answer 7

1) the null hypothesis
2) the sample statistic
3) the standard error
4) the test statistic
5) the alpha level

Question 8

the ______ is the hypothesis that is tested for rejection, and is a STATEMENT about the population indicating INITIAL BELIEF or status quo

Answer 8

the null hypothesis

Question 9

the null hypothesis assumes there is __(yes/no)__ effect on change or relationship, or that there is ___ diffrerence between treatments.

Answer 9

the null hypothesis assumes there is no effect on change or relationship between the 2 variables, and there is no difference between treatments. IF there is a change between treatments, the null hypothesis relates this back to just random chance.

Question 10

The alternative hypothesis is the ___ of the null hypothesis

Answer 10

the complement

Question 11

Non directional vs directional alternative hypothesis

Answer 11

non-directional: “a difference” “a change”

directional: “increase” “decrease”

Question 12

the goal of a study is to ____the null hypothesis and ___ the alternative hypothesis

Answer 12

the goal of a study is to reject the null hypothesis and accept the alternative hypothesis.

Question 13

What is a sample statistic?

Answer 13

a basic element of a hypothesis test. A value calculated from the sample data that allows the researcher to make inferences about a given population (ex/ sample mean, sample deviation)

Question 14

What is the standard error?

Answer 14

a basic element of a hypothesis test. the average size of the sample error/ the standard distance between a sampling statistic and the CORRESPONDING PARAMETER IN THE POPULATION.

Question 15

what is the test statistic?

Answer 15

compares the samples statistic to the null hypothesis, using standard error as a baseline.

(sample statistic- parameter of the null hypothesis)/standard error

Question 16

is the test statistic is near ___, this is an indication of NO treatment effect

Answer 16

if the test statistic is near 1. that means that the treatment sample statistic is similar to the chance results.

Question 17

is real treatment occurs, the test statistic should be _____, indicating that actual results are different than chance results and thus the null hypothesis should be rejected

Answer 17

the test statistic should be bigger than 1

Question 18

What is the alpha level?

Answer 18

The level of significance- the likely hood that the results would have occurred by chance.

Question 19

if p<0.05, then

Answer 19

then there is less than 5% chance that the results obtained by the experiment is due to chance.

Question 20

What’re the two main types of errors in hypothesis testing?

Answer 20

a type 1 error or type 2 error

Question 21

Type 1 error

Answer 21

a REJECTION ERROR/ FALSE ALARM. You accidentally accepted the alternative hypothesis but there was actually no difference in your treatment conditions or effect on the population.

Question 22

Type 2 error:

Answer 22

an ACCEPTANCE ERROR/”MISS.” The sample sata does not appear to show significance, but there is actually an effect in the population. You should have rejected the null hypothesis.

Question 23

Factors that Affect the Outcomes of the Hypothesis test

Answer 23

1) the number of scores in the sample

2) the size of variance

Question 24

T/F the larger the sample size, the more representative of the population

Answer 24

true

Question 25

T/F the sample statistic differences or correlations that are obtained with HIGH VARIANCES are less convincing than if the same results were obtained with low variance

Answer 25

true, you want low variance if you want your argument to be convincing.

Question 26

What is effect size and how is it measured?

Answer 26

an effect size provides information about the absolute SIZE of the TREATMENT EFFECT that is NOT INFLUENCED by outside factors, such as sample size. Measured using Cohens D, or as a measure of % variance.

D= sample mean difference/standard sample deviation

r^2 (when the % variance is measured for t tests
n^2 (when % variance is measured for ANOVA) or if the experiment utilizes more than one treatment mean.

Question 27

A larger Cohen’s d, the ___ difference in treatment conditions

Answer 27

the larger the difference in treatment conditions (the largest effect)

Question 28

formula for % variance

Answer 28

r^2= (t^2)/ (t^2+df), the LARGER the r^2 value, the LARGER the effect

Question 29

Confidence Interval

Answer 29

a range of values created on either side of a sample statistic (ex/ Mean, correlation) that estimates the unknown population parameter is located within an interval around a known sample statistic.

Question 30

A narrow confidence interval is _____, but less confident

Answer 30

more precise, but less confident that the interval contains the population parameter.

Question 31

a larger error= a ____ confidence interval

Answer 31

a larger error=a wider confidence interval

Question 32

Confidence Intervals are based on 3 factors, what are they?

Answer 32

1) the value of the statistic (mean, correlation)
2) the standard error for the sample statistic (larger error=wider confidence interval)
3) chosen level of confidence (increasing confidence=increasing interval)

Question 33

a larger sample population would lead to a ____ in the width of a confidence interval

Answer 33

lead to a decrease in the width of a confidence interbal. Larger samples lead to smaller standard errors, which increase the likelihood of finding a significant results and decrease the width of CI.

Question 34

Are confidence intervals a good substitute for Cohens D or R^2 value?

Answer 34

no, becaus ethe CI are influenced by sample sizes. They do not provide an unqualified measure of ABSOLUTE EFFECT SIZE.

Question 35

if r^2 for percentage variance is 0.0441, this means:

Answer 35

that 4.41% of the variance of one variable is accounted for by the OTHER variable (In a relationship between 2 VARIABLES) (if r^2 is greater than 0.25, then there is a large effect that the variance seen is caused by the other variable.

Question 36

example of measuring the effect size using percentage of variance

Answer 36

for example, studying the effects on a cholersterol drug on patients. it is expected that the patients who are givin the drug will have lower levels of cholersterol. When seeing the data, it is evident that there is variance, there are low scores mixed with high scores. however, some of these low scores can be attributed to the fact that there is a relationship between the drug and the levels of cholesterol in each participant. by knowing which patient is in the treatment group and by calculating the r^2 value, the researchers can determine how much variance in the samples is caused by the relationship between the drug and the levels of cholesterol