Exam 3 Study Guide With Answers

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Exam 3 Study Guide ANOVA 1.) What is the purpose of the ANOVA. What does it stand for and how does it accomplish its goal? The ANOVA (analysis of variance) is a parametric test that is able to located significant difference between groups (levels) by utilizing the variability between the groups and the variability within groups. The test focuses on locating the unique differences between groups but unable to understand the variability within the groups. 2.) Why is it better to use one ANOVA than allot of T tests? Using an ANOVA, we are able to look at much more that 2 groups which allows us to expand our hypothesis and learn much more about more complex groups. The importance of the ANOVA is also its ability to reduce familywise error, or the error that doing multiple t tests which will continuously stack error (the .05 level/chance of making a false positive). 3.) What is the MACRO Level of the ANOVA process? What information does it and does it not tell you? The MACRO level is the ANOVA itself which informs us if there are any significant difference between any of the groups. This though is unable to tell us exactly where that difference(s) lies. Is it between group A and B? Group B and C? or group A and C? we just don’t know. 4.) Describe variability in regards to the sums of squares. Sum of squares captures the differences between groups or individuals. This variability is the difference between individual groups or people. There is always variability in everything we do or analyze and in stats we either have variability we can explain or variability we cannot explain.

5.) What is the role of the SS total, SS between, and SS within? What makes each unique, what are the purposes of each one, how do they effect the overall analysis? SS total is ALL the variability in the analysis. SS between is the variability captured between the groups and is what we can recognize as explainable or understandable. For all the tests we did in this class there was some form of unknowable variability usually referred to as error, this is captured by the SS within. 6.) What is the micro level of the ANOVA? The micro level of the analysis is the Post hoc, comparisons, Tukey, or HSD. 7.) What is the purpose of the post hoc test? This is what is allowing us to the actually find the differences between the groups. 8.) How would you explain the eta square (effect size) for an ANOVA that looked at the differences in anxiety between class years that had an eta square of .54? a.) 54% of the variability between class years can be accounted for by anxiety. b.) 54% of the variability within anxiety can be accounted for by class years. Regression 9.) What’s the point of a regression? Regression allows us to predict future results based on past events.

10.)What is the regression equation and how does each piece mean? Y = bx + A Y is the outcome we predicted, b is the effect X has on Y, x is the number of units we have in X and A is the baseline level or average amount of Y there is. 11.)How would you explain “regression” and “residual”? Regression is the path that the data is taking. What is happening is that the data is all going into a direction, converging into one another (this convergence into a direction is called a regression or to regress into something) this regression is seen as a line or the average path taken (most optimal path). Residual is what we would usually refer to as error in this class and is the data that strays from the regression. If the regression is the path that is being followed some may stray off it or not perfectly onto it. 12.)How would you be able to tell the difference between a multiple and simple linear regression? By equation: a. Simple: Y = b(x) + A b. Multiple Y= b(x) + b(x)… + A By sentence: a. Simple: I want to predict anxiety with depression. b. Multiple: I want to predict anxiety with depression and alcohol consumption.

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13.)How would you explain the effects of multicollinearity? What are signs that it may be a concern? Multicollinearity is the statistical phenomenon where 2 or more predicters correlate with one another. Since the regression equation is just an equation it doesn’t understand that although there may be overlap within the variability that it can’t just be used by one of the predictors. Instead what happens is that the regression will literally just eliminate any shared variability which can result in less significant result and far less variance accounted for. 14.)What is homoscedasticity? Homoscedasticity is what we refer to when all the error or variability within the data is similar or not significantly different. 15.)When is someone extrapolating? What are the issues with extrapolating? There are two forms of extrapolation. The first is going out of bounds where you use units that where never found literally never happening in the past results. The other is non-occurring pairs where the units may have existed in past results, they did not coincide with one another. 16.)Explain the variance explained (effect size) of a regression if the r squared is .367. let’s pretend, because I forgot like an idiot, that we are using cups of coffee drank to predict blood pressure. a.) 36.7 percent of the variability in blood pressure is due to coffee drank. b.) 36.7 percent of the coffe drank is due to blood pressure.

c.) 36.7 percent of an individual increase or decrease in blood pressure can be accounted to the individual’s coffee consumption. d.) 36.7 percent of an individual increase or decrease in coffee drank can be accounted to the individuals blood pressure. BE able to… - Translate the SPSS output of the “Multiple Comparisons Table” - Give a simple conclusion to an ANOVA. - Be able to know when a comparison is significant or non-significant. - Explain an overall ANOVA via a plot/comparison table. - Be able to look at a regression “coefficients table” create an equation and utilize it correctly. - Explain what each piece of the regression does and contribute. For the SPSS output portion of the test look at homework 4. I will give you output of both the ANOVA and the Regression

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