Threesamma Joseph HLT-362V 9/7/2012 1. The answer is C‚ interval/ratio. The researchers analyzed the data as though it were interval/ratio level. They calculated the mean and standard deviation which is only appropriate for interval/ratio level data. 2. The mean post-test empowerment score for the control group is 97.12. This data is found explicitly in the chart of data given. 3. The baseline score mean is 14 and the post-test depression score mean is 13.36‚ meaning they were less depressed
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Name:_ Class: _GCU_HLT-362 V________________ Date: ___ □ EXERCISE 31 Questions to be Graded 1. What are the two groups whose results are reflected by the t ratios in Tables 2 and 3? Table 2 reflects the Health Promotion Program’s effects on cardiovascular risk factors and Table 3 is reflective of the program’s effects on health behavior. 2. Which t ratio in Table 2 represents the greatest relative or standardized difference between the pretest and 3 months outcomes? Is this t ratio
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1. The researchers analyzed the data they collected as though it were at what level of measurement? The answer is C‚ which is interval/ratio scale. 2. What was the mean posttest empowerment score for the control group? The mean posttest empowerment score for the control group was 97.12 3. Compare the mean baseline and posttest depression scores of the experimental group. Was this an expected finding? Provide a rationale for your answer. The data shows that there was an improvement in the mean
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Class: HTL-362V-0104 EXERCISE 20 1. Which patient scored the highest on the preoperative CVLT Acquisition? What was his or her T score? Patient 3 scored highest on the preoperative CVLT Acquisition with a T score of 62 2. Which patient scored the lowest on postoperative CVLT Retrieval? What was this patient’s T score? Patient 4 scored lowest on the postoperative CVLT Retrieval with a T score of 23 3. Did the patient in Question 2 have more of a memory performance decline than average on
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EXERCISE 29 Questions to be Graded 1. Were the groups in this study independent or dependent? Provide a rationale for your answer. The two groups were independent since they were formed based on gender with no intent to match subjects on any variable. The men and women selected didn’t share any relationship or live in the same location. 2. t = −3.15 describes the difference between women and men for what variable in this study? Is this value significant? Provide a rationale for your answer
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26 3.04 2.8 3.75 3.64 3.65 3.18 3.44 3.51 2.81 3.64 2.85 3.56 2.92 3.35 3.46 3.59 3.65 2.97 3.21 3.65 2.94 3.53 3.65 3.61 3.7 2.91 3.77 3.79 3.59 3.38 3.57 2.97 3.44 3.48 2.99 3.73 2.91 3.78 3.13 3.14 SUMMARY Groups Unemployed Part-time Full-time ANOVA Source of Variation Treatment Error Total Null hypothesis: Alternate hypothesis: Significance level: p-Value Decision: Count 25 45 130 0 0 Sum 82.110 152.050 450.130 0.000 0.000 Average 3.284 3.379 3.463 Variance 0.110 0.085 0.091 SS 0.771 18
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Analysis of Variance (ANOVA) Indian Institute of Public Health Delhi MSc CR 2013-15 Outline of the session • Need for Analysis of Variance • Concept behind one way ANOVA • Example • Non-parametric alternative When dependent variable is continuous Type of Dependent variable Type of Independent variable Number of Groups Continuous Categorical More than two Non-parametric (Wilcoxon sign rank) Paired t – test Not normal Non-parametric (Wilcoxon sign
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Variance (ANOVA) Dr. H. Johnson ANOVA • Analysis of variance (ANOVA) is a powerful hypothesis testing procedure that extends the capability of t-tests beyond just two samples. • Many types of ANOVAs‚ today we will learn about a oneway independent-measures ANOVA • Later we’ll learn one-way repeated-measures ANOVA . • We’ll also learn two-factor ANOVA after that. • These ANOVAs are by no means all of them! There are a LOT more types! One-Way ANOVA • The independent measures ANOVA is used
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Chapter 15: Introduction to the Design of Experimental and Observational Studies The Models in Analysis of Variance(ANOVA) and in Regression are different. In regression model‚ all the response and predictors are continuous (quantitative) variables. However‚ in ANOVA model‚ the response is continuous but the predictors are categorical (qualitative) variables. There are some concepts here. 1. Factor and factor level. A factor is a predictor (explanatory or independent) variable. A factor level is
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Iqra University‚ Main Campus Course: Statistical Inferences Faculty: Iftikhar Mubbashir Date: December 5‚ 2013 Fall 2013 Statistics-Walpole Chapter-12 One way Classification • • • • • • Random samples of size n are selected from each of k populations. The k populations are independent and normally distributed with means µ 1 ‚ µ 2 ‚K ‚ µ k and common variance σ 2 . We wish to derive appropriate methods for testing the hypothesis:
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