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PSY 2010 Final Exam Terms
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Terms in this set (57)
CH6 Type I error
The error that occurs when the null hypothesis is true but is rejected; Alpha level is the chance you're willing to take of making a type I error
CH6 Type II error
The error that occurs when we fail to reject the null hypothesis but should have rejected it; Beta is the probablity of making a type II error
CH6 Power
The probablity of rejecting the null hypothesis when it should be rejected; Power + Beta = 1.00
p < 0.05
reject the null hypothesis
p > 0.05
retain the null hypothesis/ fail to reject the null hypothesis
CH7 Single sample t-test
used to compare a sample mean to a specific value like a population mean
CH7 Cohen's d
a standard score that allows different effects measured by different variables to be expressed and compared with a common unit of measure
d= M - μ / s
https://toptipbio.com/cohens-d/
Cohen's d effect sizes
None ≈ 0.00
Small ≈ 0.20
Medium ≈ 0.50
Large > 0.80
CH7 r²
Tell how much impact the explantory variable has on the outcome variable
r² = (t² / t² + df) *100
CH7 Critical value of t
Value of t used to determine whether a null hypothesis is rejected or not
-df, one-tailed or two-tailed, and alpha level (0.05)
CH8 Independent samples
The selection of cases for one sample has no impact on the selection of cases for another sample
CH8 Independent samples t-test
An inferential statistical test used to compare two independent samples and an interval or ratio level dependent variable
CH8 Independent samples t-test assumptions
-Random sample
-Independence of observations
-Normality
-Homogeneity of variance
CH8 Pooled variance
The average variance for two samples
Degrees of freedom
The number of values in a sample that are free to vary
(Check the type of test to make sure you are using the correct df formula)
CH9 Longitudinal Research (Repeated-Measures Design)
Follows participants over time
CH9 Matched Pairs
Participants are grouped into sets of two based on their being similar on potential confounding variables
CH9 Paired-Samples T Test
Hypothesis test used to compare the means of two dependent samples
CH9 Pre-Post Design
Participants are measured on the dependent variable before and after an intervention
CH9 Standard Error of the Mean Difference for Difference Scores
Standard deviation of the sampling distribution of different scores; used as the denominator in the paired-samples t test
CH9 Within-Subjects Design
The same participants are measured in two different situations or under two different conditions
CH10 Analysis of Variance (ANOVA)
A family of statistical tests for comparing the means of two or more groups
CH10 One-way ANOVA
One-way ANOVA has one explanatory variable (factor)
CH10 Between-Group Variability
variablity in scores mostly due to the different treatments different groups receive
CH10 Within-group Variability
The variability that is caused by individual differences within a group
CH10 Factor
explanatory variable (consisting of multiple levels)
EX.
Factor: Handedness
Levels: Right handed, left handed, and ambidextrous
CH10 Post-hoc test
Follow up test to a statistically significant ANOVA, intended to find out if the pairs of means differ from each other
CH10 F Ratio
Ratio of between-group variability to within-group variability
F= Between Group Variability/ Within Group Variability
CH10 ANOVA Assumptions
-Random Samples
-Independence of cases
-Normality
-Homogeneity of Variance (the variance in each populations is equivalent)
CH10 ANOVA Critical Value (F table)
df between= k-1 ; columns on the F table
df within= N-1 ; rows on the F table
CH10 Sum of squares between
A sum of the squared deviation scores representing the variability between the groups
CH10 Sum of squares total
A sum of the squared deviation scores representing all the variability in the deviation scores
CH10 Sum of squares within
A sum of the squared deviation scores representing the variability within groups
CH12 Two-way ANOVA (Factorial ANOVA)
An analysis of variance in which there is more than one factor (explanatory variable)
EX. Sex and Swimming style
CH13 Pearson correlation coefficient
A statistic that summarizes the strength of a relationship between two variables
Degrees of freedom = N-2
CH13 R^2
An effect size that reveals the percentage of variability in one variable that is accounted for by the other variable
R^2 effect sizes
1% ≈ Small
9% ≈ Medium
25% ≈ Large
The closer to 0% the weaker the effect; the closer to 100% the stronger the effect
CH15 Parametric test
Statistical test used for interval or ration level outcome variables and when assumptions about the population are met (ACT scores)
CH15 Nonparametric test
Statistical test used for nominal or ordinal level outcome variables (Ex. gender)
Example of nonparametric tests: Chi-square goodness of fit, Chi-square test of independence, Mann- Whitney U test, Spearman test
CH15 Chi-Square Goodness of Fit
Nonparametric test, single sample test used to compare the distribution of a categorical outcome variable in a sample to a known population value
CH15 Chi-Square Test of Independence
Nonparametric test used to determine whether 2 or more populations of cases differ on a categorical outcome variable
CH15 Chi-Square Assumptions
-Random Sample
-Independence of observations
-Expected frequencies (each cell must have expected frequencies of at least 5)
CH14 Linear Regression
One or more predictor variables (X) are used to predict cases' scores on an outcome variable (Y)
CH14 Simple Linear Regression
One precdictor variable (X) is used to predict Y
*Only used when there is a significant correlation
CH14 Regression Line
Allows you to find a Y value for any X value
CH14 Y Prime (Y')
Another name for the predicted Y value
*Formula: Y' = bX + a
CH14 Least Squares Criterion
The best fitting line is the one that minimizes the discrepancy between the actual Y scores and the predicted Y score (Y')
CH14 Residual
The difference between each cases' actual score and the predicted score
Y (the actual score) - Y' (the predicted score)
CH14 Slope
The tilt of the line
CH14 Y-intercept
Indicates the spot where the regression line would pass through the y axis
*Y-intercept is represented by the "a" in Y= bX + a
CH14 Standard Error of the Estimate
Measure for error in prediction
Formula: Sᵧ ₋ ᵧ' = Sᵧ √ 1 - r^2
What would be the correct statistical test?
10% of the U.S. population is left handed. Several recent presidents have been left handed. This caused a cognitive psychologist to wonder if presidents were representative of the U.S. population in terms of handedness. What test should she us?
Chi-square goodness of fit
What would be the correct statistical test?
In some educational programs, there are a lot of options. One nursing program for example, allows its students to decide between (a) traditional, semester-long course; (b) online courses; (c) weekend-only course; or (d) courses that meet for 8 hours a day, 6 days in a row. The dean of the school wanted to find out if they type of course content had any impact on how much was learned. At the end of its program, she administered a 50-question, multiple-choice test about basic nursing facts. What test should she use to see if the groups differ on the mean percentage of questions answered correctly?
Between-subjects, one-way ANOVA
What would be the correct statistical test?
An ecologist obtained a random sample from 85 small rural towns and a random sample of 72 small suburban towns. For each town, he calculated pounds of trash per resident per year that went to the landfill. What statistical test should he use to see if rural and suburban residents differ in the average amount if trash they generate every year?
Independent sample t-test
What would be the correct statistical test?
The same dentist wanted to find out if his practice was unusual in terms of how many cavities his patients had. He learned that the average American has 11.23 decayed, filled, or missing permanent teeh. In his dental practice, the mean was 8.76, what a standard deviation of 3.42.
Single-sample t-test
What would be the correct statistical test?
The dentist from question 55 has a new question to contemplate. He wondered if people get most of their cavities when they are young or if they occur consistently over time. To investigate this, he decided to examine the relationship between the ages of his patients and how many of their permanent teeth were decayed, filled, or missing.
Pearsons R
What would be the correct statistical test?
A sample if students at a college were asked to classify themselves as (1) Asian; (2) Black; (3) Hispanic; (4) Native American; (5) White; or (6) other. Each person was also asked whether his or her family would consider it acceptable (yes or no) if he or she married someone from a different racial category. What statistical test should be used to see if the degree of acceptability differs among racial/ethnic categories?
Chi-square test of independence
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