Term
If a null hypothesis is true, but you reject it, you have made what type of error? 

Definition


Term
If a null hypothesis is not true, and you do not reject it, then you have made what type of error? 

Definition


Term
As alpha goes up, beta goes ? 

Definition


Term
As beta goes up, power goes ? 

Definition
down; Remember that power is 1  beta 


Term
As alpha goes up, power goes ? 

Definition


Term
Choose: anova Ftests are always/sometimes one sided/two sided for determining a pvalue. 

Definition


Term
What are the 5 assumptions for calculating ANOVA? 

Definition
Random samplesare required to be unbiased Indepedent samples If they're dependent (or repeated), you have to use repeated measures ANOVA. Independent observations w/in groups Normal distribution  (aka normal population) Equal variances (homogeneity) 


Term
When calculating ANOVA, if you have unequal variances, you have to the data. Name three ways that you would do this to your data. 

Definition
transform; log, natural log, square root 


Term
is the sum of squares (SS) What is SSB? What are other names for SSB? What is SSW? What are other names for SSW? Choose: The signal/noise should be > than the signal/noise, otherwise, we won't be able to detect the signal/noise. 

Definition
Variance; It is the variance b/w groups (it is the difference of each mean from the overall mean); SS(treatment) or SS(effects) or signal; It is the variance w/in groups; SS(error) or noise. signalnoisesignal 


Term

Definition
It is the mean square b/w groups 


Term
SSB = 43.21 SSW = 50.68 T or F: the error is greater than the treatment Why or why not? 

Definition
False, b/c you still have to divide by the df. The SSB will have a much smaller df (eg, 2) than the SSW (eg, 39). After dividing the SSB and SSW by their respective df's, you get MSB = 21.61 and MSW = 1.30. 


Term
If a comparison is not planned ahead of time, you must use even if only one posthoc comparison was performed. However, you usually perform all comparisons. 

Definition


Term
If comparisons are selected a priori, what does c =? If comparisons are selected post hoc, what does c =? 

Definition
a priori: c = number of comparisons to be made post hoc: c = total number of possible comparisons 


Term
What is the point of the Bonferroni method? 

Definition
It's like an adjusted alpha, labeled alpha'. It increases the CL for each CI in order to ensure a specific overall CL. Table 11.4 shows how conservative the bonferroni method is. 


Term
When should you use bonferroni? When should you use tukey? 

Definition
The bonferroni method should be used when comparisons are selected a priori. The Tukey method should be used when ALL comparisons are selected  it doesn't matter if they're selected a priori or post hoc. If comparisons are selected post hoc, use the Tukey method. 


Term
The same three factors that affect statistical outcomes affect ANOVA results. What are they? 

Definition
Treatment effects (differences b/w means) Variance (SSB compared to SSW) # of subjects 


Term
What are the 4 assumptions of the regression model? 

Definition
NICL Normal distribution Independence (y observations are independent of each other) Constancy of variance (the sd of y is constant for each x) Linear relationship (as opposed to exponential, curvilinear, etc) 


Term
What is residual analysis used to test? 

Definition
The assumptions of linear regression. 


Term
Correlation analysis uses pearson, r. What are the 3 assumptions of pearson? 

Definition
1) Both the ind & dep variables must b continuous. 2) Dependent variable must be rational 3)No multicollinearity (meaning ind variables cant be related to other ind variables) 


Term
What are the assumptions of B? 

Definition
1) Each y observation is independent 2) All potential y values are normally distributed for each x value 3) The std deviation of y is constant for each x 4) The sampling distribution of b is normal 


Term
What are the 4 assumptions for r? 

Definition
1) Each y observation is independent 2) The sampling distribution of both x and y are normal. 3) The std deviation of y is constant for each x 4) The sampling distribution of r is normal. 


Term
If all population means are , the sample means will be very close to each other and close to the . The weighted square differences will be , and a F will be calculated. 

Definition
equal; grand mean; small; small 


Term
ANOVA T or F: Variance cannot be negative 

Definition
True. If it is, there is too much error. 


Term
If some population means are quite different, corresponding sample means will be than each other and the . Corresponding weighted squares will be , the and will be small, and the F will be . 

Definition
quite different; grand mean; large; SSB; MSB; large 


Term
As alpha increases, Fcrit . 

Definition


Term
When is oneway ANOVA used? 

Definition
When you need to compare more than two means. More specifically, when you have one factor w/ more than two levels of the factor (ie, Drug A, Drug B, and DrugC). 


Term

Definition
Error slippage occurs when you try to do a bunch of ttests when you really should have done ANOVA. You'll think you have significant differences, but you really don't, b/c the alpha is slipping from 0.5 to 1. 


Term
Explain what X_{32} means. 

Definition
It means group 3, observation 2. 


Term
If you had two or more independent variables, what type of ANOVA would you use? 

Definition
Factorial ANOVA. The different factors may be Drugs A, B, & C (1st factor), Age (second factor), & gender (third factor). 


Term
When would you use oneway ANOVA? Name a requirement of ANOVA. 

Definition
Use oneway ANOVA when you have one factor and more than two levels. The samples in the different levels must be independent of each other. 


Term
When do you use posthoc analysis? 

Definition
When the null has been rejected and you're trying to find out which mean(s) are different. 


Term
When do you use repeated measures ANOVA? 

Definition
If measures are dependent (or repeated), you use a crossover design called repeated measures ANOVA. 


Term
What is the proper term used when your putting variances into groups? What is another name for variance? 

Definition
Partitioning Sums of Squares 


Term
SSB & SSW are weighted by the . 

Definition


Term
Choose: When pValue is greater/lesser than or equal to alpha, H_{0} cannot be rejected. 

Definition


Term
Which is worse: a type I or type II error? 

Definition


Term
A type I error is aka A type II error is aka 

Definition


Term
Define alpha What does it mean when we set out alpha to 0.05? 

Definition
It is the probability that a difference does not exist when the study shows that a difference does exist. If a study was repeated 100 times, we would be willing to be wrong 5 times. We would conclude 5 times that a difference exists when in fact it does not. 


Term
T or F: A rejection region will be larger for a onetail alpha than a twotail alpha 

Definition


Term

Definition
It is the percent chance that a difference b/w experimental grps does exist even though the study concludes no difference. 


Term
T or F: We usually look at beta after an experiment, to find out why we DIDN'T reject the null. Beta is usually set at the beginning of an experiment. Where should it be set, and why do we set it? 

Definition
True Beta should be less than or equal to 0.2. We set beta, b/c we want a certain power (at least 80% or 0.80). Notice that this isn't as strict as alpha. Remember, that we are more willing to be wrong on a type II than a type I error. 


Term
What are 3 reasons for a type II error? Which is the most common? 

Definition
Better response rate in the comparator grp Increased variance Too few subjects (most common) 


Term
If type I & type II error are inversely related, how can we reduce the chance of a type I error w/o increasing the type II error? 

Definition


Term
What is power? How do you calculate power? 

Definition
It is the percent chance that if a difference b/w grps exists that your study will detect it statistically. power = 1  beta 


Term
Name the 3 factors that affect power 

Definition
Size of treatment effect, alpha, and variability. 


Term
The size of treatment is aka 

Definition


Term
Power is affected by the "effect size". If there is a large effect, the difference is easy/difficult to detect and power is high/low. 

Definition


Term
Power is affected by the effect size. If there is a small effect, the difference will be easy/difficult to detect, type II error will be higher/lower, and power will be higher/lower. 

Definition


Term
A larger variance will result in a lower/higher power 

Definition


Term
Why is it that an increased sample size increases power? 

Definition
Because it increases df, and it controls variance (ie, SEM goes down, b/c SEM = s / sq root of n) 


Term
Why should power (and beta) be calculated a priori ? 

Definition
To determine the sample size needed for a study. 


Term
When does power not have to be calculated? 

Definition
When there is a significant difference. 


Term
T or F: Statistical significance does not equal clinical significance 

Definition


Term
When do you have to do posthoc analysis? 

Definition
If the null is rejected, you have to do posthoc analysis. Otoh, if the null accepted, the analysis is complete, b/c the variances are equal. 


Term
What is linear regression? 

Definition
To test for associations b/w variables. If independent values are given, we can use linear regression to predict the dependent variable. 


Term
Why is the simple regression equation different from the sample regression equation? 

Definition
B/c simple regression deals w/ population, which means error is included in the equation. Error is not included in the sample linear regression equation. 


Term
Least squares regression is often used to calculate linear regression. What is the least squares regression line used for? 

Definition
it sums the squared distance of the actual values to make them as close to what is predicted as possible. 


Term
If you see the least squares line equation, y = 560 + 0.14X, what does it mean? 

Definition
A 0.14 change in x will bring about a 1 unit change in Y. 


Term

Definition
It's the difference between the actual yvalue and the estimated yvalue. 


Term
What is a residual analysis used for? 

Definition
To test the assumptions of linear regression. It basically diagnoses problems w/ a model. 


Term
If you got a curve shaped residual scatter plot, would this be good or bad? Why? 

Definition
This would be bad. It would reveal that our data is not linear. We would have to transform the data. 


Term
What are the 2 problems w/ the funnel shaped residual scatter plot? 

Definition
1) The funnel reveals a problem w/ independence. 2) There is a constancy of variance. We have heteroscedasticity when we want homoscedasticity. 


Term
Why is the coefficient of determination important? The closer r^{2 }is to , the better the regression model. 

Definition
It reveals how much variation is explained by the regression line. 


Term
What is the difference b/w the coefficient of determination and the correlation coefficient? 

Definition
The coefficient of determination is the variance accounted for by a whole model. It includes the yvariables, whereas the correlation coefficient doesn't. The correlation coefficient lets you know if 2 variables are associated. The correlation coefficient b/w dependent and independent variables will generally be less than the coefficient of determination, b/c the model, which has yvariables will account for more variance. 


Term
What is multiple linear regression and what makes it different than correlation? 

Definition
It's used when you want to fit multiple independent variables to one dependent variable. Fe, the dependent variable is a students fall semester GPA. The independent variables could be GPA, ACT, ethnicity, gender, age, etc. It's different than a correlation, b/c it has predictive abilities. Fe, it can predict a dependent variable from one or more independent variables. 


Term
Statistical significance is best evaluated w/ . Clinical significance is best evaluated w/ . 

Definition
correlation coefficient (r) coefficient of determination (r^{2}) 

