ALREADY HAVE FIRST THREE ANSWERS NEED THE REST. ANOVA. Dr. Milgram is conducting a patient satisfaction survey, rating how well her patients like her on a scale of 1-10. Her patients tend to fall into three categories: “Like a lot”, “like somewhat”, and “dislike a lot”. She believes that she might get different satisfaction scores from people in each group, but (because she's not great at numbers) she wants you to do an ANOVA to be sure. She has collected data from 12 patients (three equal groups) with the following results. Group 1) “Like a lot” Mean: 8 SS: 2 N: df: Group 2) “Like somewhat” Mean: 5 SS: 6 N: df: Group 3) “Dislike a lot” Mean: 2 SS: 4 N: df: Grand Mean: 4 df Within-Group: 9 df Between-Groups: 2 Estimated Variance (S21) for Group 1: _______ Estimated Variance (S22) for Group 2: ___________ Estimated Variance (S23) for Group 3: ___________ Within-Group Estimated Variance (S2Within): ___________ Between-Group Sum of Squared Deviations: ___________ Comparison Distribution Estimated Variance (S2M): ___________ Between-Group Estimated Variance (S2Between): _________ Number of Groups:________ Number of Subjects per group: __________ Total Number of Subjects: __________ F-ratio: __________ Cut-off Score (use p<.05): ________ Final Decision: Reject the Null Hypothesis or Fail to Reject the Null Hypothesis? What does this mean for our hypotheses?
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
ALREADY HAVE FIRST THREE ANSWERS NEED THE REST.
ANOVA. Dr. Milgram is conducting a patient satisfaction survey, rating how well her patients like her on a scale of 1-10. Her patients tend to fall into three categories: “Like a lot”, “like somewhat”, and “dislike a lot”. She believes that she might get different satisfaction scores from people in each group, but (because she's not great at numbers) she wants you to do an ANOVA to be sure. She has collected data from 12 patients (three equal groups) with the following results.
Group 1) “Like a lot”
Group 2) “Like somewhat” Mean: 5 SS: 6 N: df:
Group 3) “Dislike a lot” Mean: 2 SS: 4 N: df:
Grand Mean: 4
df Within-Group: 9
df Between-Groups: 2
Estimated Variance (S21) for Group 1: _______
Estimated Variance (S22) for Group 2: ___________
Estimated Variance (S23) for Group 3: ___________
Within-Group Estimated Variance (S2Within): ___________
Between-Group Sum of Squared Deviations: ___________
Comparison Distribution Estimated Variance (S2M): ___________
Between-Group Estimated Variance (S2Between): _________
Number of Groups:________
Number of Subjects per group: __________
Total Number of Subjects: __________
F-ratio: __________
Cut-off Score (use p<.05): ________
Final Decision: Reject the Null Hypothesis or Fail to Reject the Null Hypothesis? What does this mean for our hypotheses?
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