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WorksheetsQuiz No. 4 & 5 - One-Way ANOVA and Two-Way ANOVA
Total questions: 20
Worksheet time: 26mins
The following are assumptions for ANOVA except:
Variance must be homogenous
There should be 4 or more independent groups
Data must be normally distributed
Randomly selected
ANOVA testing is used for ...
Test for one mean
Test for two means
Test for three or more means
Test for independence between two variables
Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:
A researcher want to determine whether there is an interaction between physical activity level and gender on blood cholesterol concentration in children.
one-way ANOVA test
two-way ANOVA test
Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:
A group of psychiatric patients are trying three different therapies: counseling, medication and biofeedback. They want to see if one therapy is better than the others.
one-way ANOVA test
two-way ANOVA test
ANOVA stands for ...
Analysis of Variation
Analysis of Variance
Analysis of Variability
A Non-Visual Analysis
Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:
A nutritionist is studying the effects of diet on cholesterol in men and women. She has data which reports cholesterol levels for men and women for three different diets (low-fat low calorie, Adkins diet, Mediterranean diet).
one-way ANOVA test
two-way ANOVA test
This test is the nonparametric alternative of One-Way ANOVA often used when the level of measurement is ordinal.
Kruskal-Wallis Test
Wilcoxon Test
Mann-Whitney U Test
Binomial Test of Equality
Which is NOT Assumptions and Design Consideration for One-Way ANOVA
Normal distributed population
Independence of error
Homogeneity of viscoscity
Data scale
Given Null hypothesis H0: µ1 = µ2 = µ3 ……….. µk. What does the "K" stand for?
Number of levels
Number of row data
Number of column data
Number of variables
Given the alternative hypothesis Ha: µ1 ≠ µ2 ≠ µ3 ≠ …….. µk. Which are the correct interpretations?
The population mean is not same in all the groups
At least one group is different from another
Population means and hypothesized valueare equal
The population mean is same in all the groups
This test is used when comparing groups on two different categorical variables which focuses on the interpreting main effects and interaction effects.
One-way ANOVA
Two-way ANOVA
One-way t-Test
Two-way t-Test
In two-way ANOVA, this effect is where the factorial analysis looks for significant changes in the dependent variable as a result of two or more of the independent variables working together
Main Effect
Sub Effect
Interaction Effect
Outcome Effect
In two-way ANOVA, this effect is where the use of two-way ANOVA permits the evaluation of each independent variable’s effects on the dependent variable
Main Effect
Sub Effect
Interaction Effect
Outcome Effect
A corn farmer is interested in reducing the number of days it takes for his corn to silk. He has decided to set up a controlled experiment that manipulates the nominal variable “fertilizer,” having two categories: 1 = limestone and 2 = nitrogen. Another nominal variable is “soil type,” with two categories: 1 = silt and 2 = peat.
What is the dependent variable?
Number of Days until the corn begins to silk - Scale
Fertilizer (With categories: Limestone and Nitrogen) - Nominal
Soil Type (With categories Silt and Peat) - Nominal
A corn farmer is interested in reducing the number of days it takes for his corn to silk. He has decided to set up a controlled experiment that manipulates the nominal variable “fertilizer,” having two categories: 1 = limestone and 2 = nitrogen. Another nominal variable is “soil type,” with two categories: 1 = silt and 2 = peat.
What factorial anova best describes this scenario?
2x2 Factorial Anova
2x4 Factorial Anova
4x4 Factorial Anova
A corn farmer is interested in reducing the number of days it takes for his corn to silk. He has decided to set up a controlled experiment that manipulates the nominal variable “fertilizer,” having two categories: 1 = limestone and 2 = nitrogen. Another nominal variable is “soil type,” with two categories: 1 = silt and 2 = peat.
What factorial anova best describes this scenario?
2x2 Factorial Anova
2x4 Factorial Anova
4x4 Factorial Anova
A corn farmer is interested in reducing the number of days it takes for his corn to silk. He has decided to set up a controlled experiment that manipulates the nominal variable “fertilizer,” having two categories: 1 = limestone and 2 = nitrogen. Another nominal variable is “soil type,” with two categories: 1 = silt and 2 = peat.
What "are" the independent variables?
Number of Days until the corn begins to silk - Scale
Fertilizer (With categories: Limestone and Nitrogen) - Nominal
Soil Type (With categories Silt and Peat) - Nominal
A social media analyst whats to find out if the use of social media (low, medium, high) can affect the difference of hours of sleep per night. The analyst plans to use one-way ANOVA for this test.
What would be your independent variable?
Social Media Use (Categories: Low, Medium, High) - Nominal
Difference in Hours of Sleep per Nights (Scale)
Social Media Use (Categories: Low, Medium, High) - Scale
Difference in Hours of Sleep per Nights (Nominal)
A social media analyst whats to find out if the use of social media (low, medium, high) can affect the difference of hours of sleep per night. The analyst plans to use one-way ANOVA for this test.
What would be your dependent variable?
Social Media Use (Categories: Low, Medium, High) - Nominal
Hours of Sleep per Nights (Scale)
Social Media Use (Categories: Low, Medium, High) - Scale
Hours of Sleep per Nights (Nominal)
When determining whether any of the differences between the means are statistically significant, you will compare the p-value to your significance level to assess the null hypothesis.
Which of the following statements is true?
P-value ≤ α: The differences between some of the means are statistically significant
P-value > α: The differences between some of the means are statistically significant
P-value ≤ α: The differences between some of the means are not statistically significant
