Posted: February 25th, 2023

Problem 1: Probability Using Standard Variable z and Normal Distribution Table

Problem 1: Probability Using Standard Variable z and Normal Distribution Tables
Variables are the things we measure. A hypothesis is a prediction about the relationship between variables. Variables make up the words in a hypothesis.
In the attention-deficit/hyperactivity disorder’s (ADHD’s) hypothetical example provided in the tables below, the research question was: What is the most effective therapy for ADHD? One of the variables is type of therapy. Another variable is change in ADHD-related behavior, given exposure to therapy. You might measure change in the mean seconds of concentration time when children read. This experiment is designed to obtain children’s concentration times while they read a science textbook and to find out whether the therapy used worked on any of the children.
Use the stated µ and σ to calculate probabilities of the standard variable z to get the value of p (up to three decimal places). In addition, respond to the following questions for each pair of parameters:
Which child or children, if any, appeared to come from a significantly different population than the one used in the null hypothesis?
What happens to the “significance” of each child’s data as the data are progressively more dispersed?
In addition to the above, write a formal statement of conclusion for each child in APA style. A report template is provided for submission of your work.
Note: Tables 1 and 2 are practice tables with answers. Tables 3 and 4 are the assignment tables for you to work on.
Table 1 (µ = 100 seconds and σ = 10)
Child Mean seconds of concentration in an experiment of reading z-score
(z = [X – µ]/σ) p-value
1 75 -2.50 0.0
2 81 -1.90 0.0
3 89 -1.10 0.1
4 99 -0.10 0.4
5 115 1.50 0.0
6 127 2.70 0.0
7 138 3.80 <0.0 8 139 3.90 <0.0 9 142 4.20 <0.0 10 148 4.80 <0.0 Table 2 (µ = 100 seconds and σ = 20) Child Mean seconds of concentration in an experiment of reading z-score (z = [X – µ]/σ) p-value 1 75 -1.25 0.1 2 81 -0.95 0.1 3 89 -0.55 0.2 4 99 -0.05 0.4 5 115 0.75 0.2 6 127 1.35 0.0 7 138 1.90 0.0 8 139 1.95 0.0 9 142 2.10 0.0 10 148 2.40 0.0 Table 3 (µ = 100 seconds and σ = 30) Child Mean seconds of concentration in an experiment of reading z-score p-value 1 75 2 81 3 89 4 99 5 115 6 127 7 138 8 139 9 142 10 148 Table 4 (µ = 100 seconds and σ = 40) Child Mean seconds of concentration in an experiment of reading z-score p-value 1 75 2 81 3 89 4 99 5 115 6 127 7 138 8 139 9 142 10 148 Refer to the Assignment Resources on this page for Two Independent Samples of t-Test to view an example of probability using standard variable and normal distribution tables. The same resource is also available under lecture Estimation and Hypothesis Testing. Problem 2: Two-Sample Inferences A two-sample inference deals with dependent and independent inferences. In a two-sample hypothesis testing problem, underlying parameters of two different populations are compared. In a longitudinal (or follow-up) study, the same group of people is followed over time. Two samples are said to be paired when each data point in the first sample is matched and related to a unique data point in the second sample. This problem demonstrates inference from two dependent (follow-up) samples using the data from the hypothetical study of new cases of tuberculosis (TB) before and after the vaccination was done in several geographical areas in a country in sub-Saharan Africa. Conclusion about the null hypothesis is to note the difference between samples. The problem that demonstrates inference from two dependent samples uses hypothetical data from the TB vaccinations and the number of new cases before and after vaccination. Table 5: Cases of TB in Different Geographical Regions Geographical regions Before vaccination After vaccination 1 85 11 2 77 5 3 110 14 4 65 12 5 81 10 6 70 7 7 74 8 8 84 11 9 90 9 10 95 8 Using SPSS, and perform the analysis, then complete the following: Construct a one-sided 95% confidence interval for the true difference in population means. Test the null hypothesis that the population means are identical at the 0.05 level of significance. In addition, in a Microsoft Word document, provide a written interpretation of your results in APA format. Problem 3: Cross-Sectional Study In a cross-sectional study, the participants are seen at only one point of time. Two samples are said to be independent when the data points in one sample are unrelated to the data points in the second sample. The problem that demonstrates inference from two independent samples will use hypothetical data from the American Association of Poison Control Centers. There are two groups of independent data collected in different regions, which also calls for a t-test. The numbers represent the number of recorded cases of poisoning with chemicals in the homes of 100,000 people in two regions. Table 6: Cases of Poisoning With Chemicals Year Region 1 Region 2 1 150 11 2 160 10 3 132 14 4 110 12 5 85 10 6 45 11 7 123 9 8 180 11 9 143 10 10 150 14 Formulate a null and an alternative hypothesis for a two-sided test. Conduct the test at the 0.05 level of significance. In addition, in a Microsoft Word document, provide a written interpretation of your results in APA format.

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