Symbols
Tests
Equations
Interpreting data
Definitions
100
μ
What is Mu – population symbol for Mean Measure of central tendency
100
Chi-squared
Used for categorical data IV measured only in Nominal or Ordinal data – data are tallies or frequency counts Each observation is independent of every other observation The categories are exhaustive (inclusive) Data are qualitative
100
X^2=∑(O-E)^2/E
What is Formula for Chi-square: O – Observed number of tallies in each category E – Expected number of tallies given the hypothesized population distribution
100
Interpreting Chi-squared
What is X2 (obs) > X2 (crit) If Observations are greater than Critical value we Reject the Null Hypothesis X2 (obs) < X2 (crit) If Observations are less than Critical value we Retain Null Hypothesis
100
Goals of Research
What is Examine if there is a systematic (meaningful) relationship between two variables (IV & DV) Control bias to understand what caused the relationship or change in behaviour Establish generalizability
200
σ
What is Sigma – population symbol for standard deviation Spread of population
200
z - score
What is the value of an observation exposed in standard deviation units. Calculated by taking the observation, subtracting from it the mean of all observations, and dividing the results by the standard deviation of all observations. A new distribution is created that has a mean of 0 and SD of 1.
200
σ_M= σ/√n
What is Standard deviation of the Sampling Distribution; STANDARD ERROR SD for means of samples decreases by the inverse of square root of sample size
200
Interpreting t-test
What is tobs>tcrit; pobs
200
Probabilistic sampling procedures
What is - Simple random - Systematic sampling with random start - Stratified random (proportional and disproportional) - Multistage cluster
300
p
What is Rho – population symbol for correlation
300
Confidence Intervals
For a given statistic calculated for a sample of observations (e.g. mean), the CI is a range of values around that statistic that are believed to contain, with a certain probability (eg. 95%), the true value of that statistic (ie, the population value).
300
z=(M-μ)/(σ/√n)
What is Equation for z distributions Non-directional
300
Interpreting CI’s
What is If parameter falls outside the CI, then reject the null If parameter falls within the CI, retain the null
300
Central Limit Theorem
What is As sample size increases, the sampling distribution of the means of the samples approaches normality even if the parent distribution is not normal The mean of this distribution approaches the mean of the population SD for this distribution is SD=√n which is called STANDARD ERROR
400
α
Alpha – type I error Probability of making a type I error OR Rejecting H0 when the null is TRUE and should be retained
400
t-test
Used to test whether a regression coefficient b is significantly different from zero. In experiments used to test whether the differences between two means are significantly different from zero.
400
M-z(cv.05) (σM )<μ
What is equation for confidence interval
400
Levene’s Homogeneity of Variance Interpretation
What is f-statistic, the assumption of the variance of one variable is stable to all levels of another variable p<0.05 = REJECT the Null hypothesis that variances are equal t-test if n1=n2 then homogeneity of variance is not an issue. If no HOV adjust denominator of equation If variance is 4X variance of 2 groups use unequal variance test
400
Power
What is A measure of sensitivity Sensitivity of the experiment to detect a real effect of the independent variable (IV) The ability of your experiment to reject the null if there is a treatment effect Correctly rejecting the false H0 Probability of not making a type 2 error
500
β
Beta – probability of making a Type 2 error OR Retaining the H0 when the null is FALSE and should be rejected
500
ANOVA
Analysis Of Variance Uses the f-ration to test the overall fit of a linear model tends to be defined in terms of group means, and the resulting ANOVA is therefore an overall test of whether group means differ. Compare two or more means at once. Is there a significant difference among the them
500
t_obs=(M-μ)/s_Xbar
What is equation for t-test; Numerator is the difference between means and reflects the ‘effect’ – explained variability Denominator is the value for the SD estimate of appropriate sampling distribution (SE) – reflects error or unexplained variability
500
Effect Size
What is Cohen’s D Measure of practical or clinical significance Trivial: <0.20 Small: 0.20-0.50 Medium: 0.51-0.80 Large: >0.80
500
Non-probabilistic sampling procedures
What is - Purposive - Snowball - Haphazard or convenience - Quota
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