(Two-way ANOVA)
Research scenario: A researcher is studying how calories (1 = regular, 2 = low, 3 = zero) and price (1 = below $2.5, 2 = above $2.5) impact consumers’ purchase intentions toward energy drink?
RQ: How calories and price impact consumers’ purchase decisions?
IV 1: Calories (3 levels: regular, low, zero)
IV 2: Price (2 levels: below $2.5, above $2.5)
DV: Purchase intentions
Purchase intentions is measured by the following scale
How likely are you to buy energy drink in the future?
Very unlikely Very likely
1 … 7
Questions:
What is the factorial design in this research scenario?
2. Please state the null and alternative hypotheses for the main effect of calories on consumers’ purchase intentions
Please state the null and alternative hypotheses for the main effect of price on consumers’ purchase intentions
4. Please state the null and alternative hypotheses for the interaction effect between calories and price on consumers’ purchase intentions
(Correlation & Simple linear regression)
A correlation analysis was conducted between student’s IQ score and achievement test score. Below is the SPSS output. Please fill in the blanks based on the SPSS output.
Correlation coefficient was computed between __ and __ The result was _______(significant /not significant) Pearson correlation coefficient (r) is _.___, p ______.
There is a _ ______(positive/negative) and ____ __ (weak/moderate/strong) correlation between IQ score and achievement test score, when IQ score increases, the achievement test score __ ______(increases/decreases).
*Please use this table to evaluate the strength of the relationship
A salesperson for a large car brand wants to determine whether there is a relationship between income and the price an individual pay for a car, so he runs a simple linear regression using income as the predictor and the price an individual pay for a car as the outcome. Below is the SPSS output. Please fill in the blanks based on the SPSS output.
A simple linear regression was conducted to predict _____ _____________________________by _____ ________________________. Multiple correlation coefficient (R) is _______, which indicates a __ _____(positive/negative) and __ ____ (weak/moderate/strong) relationship between income and the price an individual pays for a car.
The intercept (b0) is _______________. The estimated slope (b1) is ___________, which was _____________________ (statistically significant/not significant), p is _______. It means as the income increases by $1, the price an individual pays for a car ________(increases/decreases) by $ ______.
Please use this table to evaluate the strength of the relationship
If our regression equation is STC103 final score (Ŷ) = 45+0.90×midterm exam score (x), what is the predictor?
a) STC103 final score
b) 45
c) 0.90
d) midterm exam score
If our regression equation is STC103 final score (Ŷ) = 45+0.90×midterm exam score (x), what is the intercept?
a) STC103 final score
b) 45
c) 0.90
d) midterm exam score
If our regression equation is STC103 final score (Ŷ) = 45+0.90×midterm exam score (x), what is the slope?
a) STC103 final score
b) 45
c) 0.90
d) midterm exam score
What does the slope mean (using your answer on Q3)?
If we know that the regression coefficient of predictor A is statistically significant and positive, we know that
a) with the increase of A, the outcome/dependent variable increases
b) with the increase of A, the outcome/dependent variable decreases
c) there is no relationship between the predictor A and the outcome/dependent variable.
d) none of the above.
Short Answer Questions
What is the difference between correlation and simple linear regression?
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