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Psyc 210 Final
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Gravity
Terms in this set (63)
Population
The entire group that the researchers are interested in describing and drawing conclusions about
Sample
Subset of population; the group that you actually study and from which you collect data
Variable
Any characteristic, behavior, or condition that can occur in differing amounts or kinds
Data
Measurements collected in research; often scores, but may be ranks, categories, or types
Statistics
A set of mathematical procedures and techniques used to make sense of data
Descriptive statistics
Used to organize, summarize, and simplify data in order to identify meaningful patterns in the data
Inferential statistics
Used to draw conclusions from the sample data in order to make statements about the population of interest
Independent variable
The causal variable that we either manipulate or observe to try to determine its effects on the dependent variable (is not affected by another variable)
Dependent variable
The outcome we wish to describe and explain (outcome depends on some other variable)
Continuous variable
Potentially, there is an infinite number of values between two adjacent values; can take on a full range of values, including numbers out to many decimal places; fractional values are meaningful amounts of the variable (scale, quantitative, numerical)
Discrete variable
Only whole values or categories with no fractional amounts between them (qualitative, categorical, classification, count)
Nominal scale
Names; they label observations but do not provide quantitative information
Ordinal scale
Rank order; measurements provide some info about relative amount or magnitude; indicate more or less but not exactly how much; the exact amount of difference between adjacent values cannot be determined
Interval scale
A series of scores that are organized in an ordered sequence with equal intervals between values on the measurement scale; no absolute zero point
Ratio
A series of scores that are organized in an ordered sequence with equal intervals between values on the measurement scale; have an absolute, real zero point
Frequency distributions
Organization of data to show the number of times each score occurs in the sample
Platykurtic
Flat and broad distribution
Leptokurtic
Thin and sharply peaked distribution
Percentile rank of a score
Percentage of individuals in the distribution with scores at or below the score (=cumulative percentage)
Percentile
Usually refers to a score corresponding to a particular percentile rank
Bar graph
For discrete data, vertical bar centered over each score or interval, adjacent bars do not touch
Frequency histogram
For continuous data, vertical bar centered over each score or interval, adjacent bars touch
Frequency polygon
For continuous data, point centered over each score or interval on the X-axis, points are connected by straight lines, ends of polygons are closed by dropping line down to X-axis
Mean
Arithmetic average; the balance point, or fulcrum, of the distribution
Median
The score that divides the distribution in half, such that half of the scores are greater and half of the scores are less than it
Mode
The most frequently occurring score in the distribution
Variability
Differences among scores; the spread or dispersion of scores
Range
Distance between the highest and lowest scores (=highest score-lowest score)
Interquartile range (IQR)
The range of the middlemost 50% of scores; range after eliminating the highest 25% of scores and lowest 25% of scores; the distance between the 1st quartile and the 3rd quartile
Standard deviation
Average distance of scores from the mean (=X-M)
Degrees of freedom
Number of scores that are unrestricted, can take on any value in calculating the statistic
z score
Indicates the distance of a raw score from the mean in standard deviation units (=X-M/s)
Standardized distribution
Distribution of scores that has been transformed to create pre-determined values for mean and standard deviation
Normal distribution
A family of frequency distributions which are symmetrical, unimodal, with asymptotic tails (never reach frequency of 0)
68-95-99.7 Rule
The numbers in this rule refer to the percentages of normal distribution within 1, 2, and 3 standard deviations of the mean
Correlation coefficient
Statistical measure of the relationship between two variables
Coefficient of determination: r^2
Proportion of variance in one variable that is accounted for by the relationship with the other variable; also known as proportion of explained variance
Coefficient of nondetermination:(1-r^2)
Proportion of variance not accounted for
Regression
Statistical technique for determining the best-fitting straight line of a set of data
Equation of the regression line
Y{hat} = bX + a
Standard error of the estimate
Average amount of error in the predictions; the mean distance of the actual values of Y from the best fitting line; a measure of how accurately the regression line predicts the Y values
Beta (standardized regression coefficient)
Indicates the predicted change in the dependent variable in standard deviation units, given a one standard deviation increase in the independent variable when all other IVs are held constant
R^2
Proportion of variance in the DV that is explained by the set of independent variables included in the multiple regression
Probability
The likelihood of an outcome occurring by chance (# of ways it could happen/ total # of possible events)
Sampling distributions
Theoretical distribution that shows
1) all possible values of the statistic
2) the frequency of each possible value of the stat from sample size n when:
a) sampling is random with replacement
b) all possible samples have been taken from the population
Used to determine the likelihood of a value of that statistic occurring by chance alone
Sampling distribution of r
Shows each possible value of r for:
sample size n & all possible random samples
from a population in which variables X & Y are not relation (rho=0)
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 our sample results
Steps of hypothesis testing
1) State the hypotheses
2) Set alpha
3) Collect data and compute sample statistics
4) Determine p, the probability of obtaining the sample statistic by chance alone
5) Make a decision about the null hypothesis
State conclusion with correct format.
Type 1 error
Incorrect rejection of the null hypothesis
Type 2 error
Incorrect acceptance of the null hypothesis
Power
The likelihood of correctly detecting a real effect (correct rejection of null); in other words, the likelihood of getting statistically significant result
Effect size
A measure of the magnitude of the research result
Estimation
Inferential technique to use sample statistics to estimate the value of a population parameter
Confidence interval
A range of values that has a specific probability of containing the value of the population parameter
t-test
Used when the DV is continuous, the IV is discrete, and the sample result consists of one or two means
(t measures the mean difference in standard deviation units; is an index of difference between distributions/groups; means relative to spread of scores)
Steps of hypothesis testing for a t-test
1) State hypotheses
2) Set alpha
3) Collect data and compute t
4) Determine the probability of t
5) Make decision about null hypothesis
Cohen's d
A measure of effect size (in t-tests) that assesses the difference between two means in terms of standard deviation, not standard error
ANOVA
Hypothesis test used to evaluate mea differences between more than two groups
F
A measure of differences between groups relative to error, influenced by the differences between means as well as the spread of scores in each group
Steps of hypothesis testing for one-way ANOVA
1) State hypotheses
2) Set alpha
3) Collect data and compute F
4) Determine probability of F
5) Make a decision about hypotheses
Post hoc tests
Pairwise comparisons made after finding that F is significant. Used to determine which pairs of means are significantly different
eta^2
Effect size for ANOVA; proportion of variance in the DV that is accounted for by the IV
Two-way ANOVA
Hypothesis test used when there are two independent variables used to create groups; the dependent variable is continuous
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