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Analyze Anova for Test Scores

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Not sure how to set this up, or how to calculate Anova analysis.
The team wants to investigate whether or not test scores are significantly related to
to different teaching styles including
a) lecture style,
b) group learning,
c) self directed and
d) distance learning.

1. Use the data provided to conduct a one-way analysis of variance of the data.
2. Determine whether or not teaching style has an impact on student test scores at the 5% significance level.
Areas to calculate: ANOVA Analysis Of Variance
Correction for the Mean
df degrees of freedom
F F statistic used to compare with the F-table value ('critical value')
MS Mean Square
SS Sum of Squares

So what must be found is:
What is the SUM of SQUARES (SS) for FACTOR?
What is the SUM of SQUARES (SS) for ERROR?
What is the SUM of SQUARES (SS) TOTAL?
What is the Degrees of Freedom (Df) for FACTOR?
What is the Degrees of Freedom (Df) for the ERROR term?
What is the Degrees of Freedom (Df) TOTAL?
What is the MEAN SQUARED (MS) for FACTOR?
What is the MEAN SQUARED (MS) for the ERROR term?
What is the F Calculated value?
What is F Critical value (from the table)?

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Solution Summary

The solution analyzes ANOVA for test scores to examine different teaching styles.

Solution provided by:
Changping Wang, MA
Education
  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
  • "Thank you"
  • "Thank you very much for your valuable time and assistance!"
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