In one-way ANOVA,

a. list and interpret the three sums of squares.

b. state the one-way ANOVA identity and interpret its meaning with regard to partitioning the total variation among all the data.

Short Answer

Expert verified

(a) Three sum of squares are SSE, SSTR, and SST.

(b) The One-way ANOVA identity isSST=SSTR+SSE.

Step by step solution

01

Part(a) Step 1: Definition

The statistical approach of analysis of variance, or ANOVA, divides observed variance data into multiple components for use in additional tests. For three or more groups of data, a one-way ANOVA is used to learn more about the relationship between the dependent and independent variables.

02

Part(a) Step 2: Explanation

SSE stands for the erroneous sum of squares. It identifies the cause of variation's inaccuracy.

SSTR stands for the sum of squares treatment. It identifies the source of difference in treatment.

SST stands for a total sum of squares. It shows the entire amount of variation.

03

Part(b) Step 1: Definition

The statistical approach of analysis of variance, or ANOVA, divides observed variance data into multiple components for use in additional tests. For three or more groups of data, a one-way ANOVA is used to learn more about the relationship between the dependent and independent variables.

04

Part(b) Step 2: Explanation

The overall sum of the squares is equal to the sum of the treatment and error squares added together.

SST=SSTR+SSE

The total variation among all observations is separated into two components, as shown by the preceding equation. One factor is variance across samples, while the other is variation within sample components.

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Most popular questions from this chapter

a. Obtain individual normal probability plots and the standard deviations of the samples.

b. Perform a residual analysis.

c. Use your results from parts (a) and (b) to decide whether conducting a one-way ANOVA test and the data is reasonable. If so, also do parts d-f.

d. Use a one-way ANOVA test to decide, at the 5%significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken.

e. Interpret your results from part (d).

Weight Loss and BMI. In the paper "Voluntary Weight Reduction in Older Men Increases Hip Bone Loss: The Osteoporotic Fractures in Men Study" (Journal of Clinical Endocrinology & Metabolism, Vol. 90, Issue 4. Pp. 1998-2004), K. Ensrud et al. reported on the effect of voluntary weight reduction on hip bone loss in older men. In the study, 1342 older men participated in two physical examinations an average of 1.8years apart. After the second exam, they were categorized into three groups according to their change in weight between exams: weight loss of more than 5%, weight gain of more than , and stable weight (between 5%loss and5% gain). For purposes of the hip bone density study, other characteristics were compared, one such being body mass index (BMI). On the Weissstats site, we provide the BMI data for the three groups, based on the results obtained by the researchers.

An F-curve has df=(24,30). In each case, find the F-value having the specified area to its right.

a.0.05

b.0.01

c.0.025

SAMPLE 1SAMPLE 2SAMPLE 3
1104
9416

810

6

2

Figure 13.7 shows side-by-side boxplots of independent samples from three normally distributed populations having equal standard deviations. Based on these boxplots, would you be inclined to reject the null hypothesis of equal population means? Why?

Fill in the missing entries in the partially completed one-way ANOVA table

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