**Problem Description:**A psychologist at a private psychiatric hospital conducted a study to determine whether there was any significant difference in the length of stay for patients with different categories of diagnosis. The data collected included the length of stay (in weeks) for the last four patients in each of three major categories:- **Affective Disorders:** - 7 weeks - 6 weeks - 5 weeks - 6 weeks- **Cognitive Disorders:** - 12 weeks - 8 weeks - 9 weeks - 11 weeks- **Drug-Related Conditions:** - 8 weeks - 10 weeks - 12 weeks - 10 weeks**Means and Sums of Squares:**- $ M_1 = 6 $, $ SS_1 = 2 $- $ M_2 = 10 $, $ SS_2 = 10 $- $ M_3 = 10 $, $ SS_3 = 8 $- $ SS_{Between} = 42.67 $**Tasks:**a. **Test to Perform:** - Conduct an ANOVA (Analysis of Variance).b. **List the Hypotheses:** - Null Hypothesis ($ H_0 $): There is no significant difference in the length of stay among the three diagnosis categories. - Alternative Hypothesis ($ H_1 $): There is a significant difference in the length of stay among the three diagnosis categories.c. **Decision Rule:** - Decide on the significance level (commonly 0.05) to determine the critical value. Reject the null hypothesis if the calculated F-value is greater than the critical F-value from the F-distribution table.d. **Perform the ANOVA:** - Calculate the necessary values for the ANOVA table.e. **Complete the ANOVA Table:**| Source | SS | df | MS | F ||-----------|----------|-----|-------|------|| Between | 42.67 | 2 | | || Within | | | | || Total | | | | |- Note: Fill in MS (Mean Square) and F-ratio after computing them.f. **Report your ANOVA result

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Answered: 5. A psychologist at a private…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Department of Research and Development of Unilever Sdn Bhd has conducted a study to improve the quality of production line by measured the weight (in ounces) of 50 bars of soap. The results are as shown in Table 2(b). Table 2(b) Weight of soap 11 12 12 12 13 13 13 13 13 14 14 14 14 14 15 15 15 15 15 15 15 15 15 16 16 16 16 16 16 16 16 16 17 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 19 20 (1) Calculate the mean, standard deviation and variance. (ii) By using 6 of class interval, construct a histogram for this data.
1) a.What is/are the appropriate measure(s) of central tendency for each of the variables in Columns B-F? Explain your answers in no more than two sentences each. b. Calculate the measures of central tendencies above c. Imagine that a 21st run is added to your dataset. See the table below for its data Run Eth. Gly. Acid. Temp pH 21 18.2 7.2 2.1 18 4.2 d. Do these data points change your choices of central tendency reported in Question 2b? Explain your answer. Attached dataset; a b c d e f Run Ethanol Glycerol Acidity Temp pH 1 4.8 3.5 0.84 24 3.8 2 9.6 7.3 0.27 24 3.8 3 10.2 7.2 0.27 24 3.8 4 8.5 5.1 0.55 24 3.8 5 7.3 3.2 0.68 24 3.1272 6 4.8 1.2 1.24 30 4.2 7 7.9 4.4 0.65 18 3.4 8 6.7 4.3 0.65 30 3.4 9 9.8 6.9 0.47 24 3.8 10 10.2 7.2 0.32 24 3.8 11 9.8 5.8 0.51 24 3.8 12 10.2 7.5 0.28 24 3.8 13 8.2 5.1 0.49 18 4.2 14 7.1 3.9 0.6 18 3.4 15 8.2 4.8 0.46 13.908 3.8 16 5.6 3.3…
For each of the following epidemiological scenarios, draw a DAG that represents the relationships between the variables: A researcher is studying the association between experiencing childhood abuse (A) and the occurrence of depression (D) as an adult. She has reason to believe that alcohol consumption (C) may mediate the relationship between (A) and (D).
Describe as specifically as possible the following for this study: 1.Observational Unit 2.Experimental Unit 3.Variables - Specify which are quantitative and which are categorical and furtherclassify each as Nominal, Ordinal, Interval, or Ratio. Specify which are explanatoryand which are response variables.
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Among the literature on quitting smoking are data detailing the relative successfulness of people of different ages in quitting smoking. A study of 400 adults who began various smoking-cessation programs produced the data in the table below. In the table, each participant is classified according to two variables: length of their smoking cessation period ("Less than two weeks", "Between two weeks and one year", or "At least one year") and age ("21-34", or "35 and over"). In the table, "less than two weeks" means that the individual returned to smoking within two weeks of beginning the program; "between two weeks and one year" means that the individual lasted the first two weeks without smoking but retuned to smoking within a year; and "at least one year" means that the individual has not smoked for at least a year since beginning the program. The table is a contingency table whose cells contain the respective observed frequencies of classifications of the 400 smokers. In addition, three…
The authors of a paper compared two different methods for measuring body fat percentage. One method uses ultrasound, and the other method uses X-ray technology. Body fat percentages using each of these methods for 16 athletes (a subset of the data given in a graph that appeared in the paper) are given in the accompanying table. You can assume that the 16 athletes who participated in this study are representative of the population of athletes. Athlete X-ray Ultrasound 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 5.00 8.00 9.25 12.00 17.25 29.50 5.50 6.00 8.00 13.50 9.25 11.00 12.00 14.00 17.00 18.00 4.25 4.75 9.00 11.75 17.00 27.50 6.50 6.75 8.75 14.50 9.50 12.00 12.25 15.50 18.00 18.25 Use these data to estimate the difference in mean body fat percentage measurement for the two methods. Use a confidence level of 95%. (Use μ = MX-ray-Multrasound. Round your answers to three decimal places.) × % Interpret the interval in context. O There is a 95% chance that the true mean body fat percentage…
To test for any significant difference in the number of hours between breakdowns for four machines, the following data were obtained. Machine1 Machine2 Machine3 Machine4 6.7 8.7 11.1 9.8 8.0 7.5 10.3 12.9 5.4 9.5 9.6 12.1 7.6 10.1 10.2 10.9 8.6 9.2 9.0 11.3 7.5 9.6 8.6 11.4 Use the Bonferroni adjustment to test for a significant difference between all pairs of means. Assume that a maximum overall experimentwise error rate of 0.05 is desired. Find the value of LSD. (Round your comparisonwise error rate to three decimal places. Round your answer to two decimal places.) LSD = Find the pairwise absolute difference between sample means for each pair of machines. x1 − x2= x1 − x3= x1 − x4= x2 − x3= x2 − x4= x3 − x4= Which treatment means differ significantly? (Select all that apply.) There is a significant difference between the means for Machine 1 and Machine 2.There is a significant difference between the means for Machine 1 and Machine 3.There is a significant…
5. An article in Agricultural Engineering (December 1964, pp. 672-673) described an experiment in which the daily weight gain of swine is evaluated at different levels of housing temperature. The mean weight of each group of swine at the start of the experiment is considered to be a nuisance factor. The data from this experiment are as follows: Mean Weight (lbs) Housing Air Temperatures (°F) 100 50 60 70 80 90 1.37 1.58 2.00 1.97 1.40 100 0.39 150 1.47 1.75 2.16 1.82 1.14 -0.19 200 1.19 1.91 2.22 1.67 0.88 -0.77 Does housing air temperature affect mean weight gain at a = 0.05?

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