# I'M NOT LAZY, project is due tonight and.. please help, its truly appreciated ( ◡‿◡ *)

I use STATCRUNCH through the Pearson - MyStatLab

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An educator conducted an experiment to test whether new directed reading activities in the classroom will help elementary school pupils improve their reading ability. She arranged for a third grade class of 21 randomly selected students to follow these activities for an 8-week period. A control classroom of 23 randomly selected third graders followed the same curriculum without the activities. None of the participating students knew what class (activities or not) they belong to. At the end of the 8 weeks, all students took a Degree of Reading Power (DRP) test. Assume that the samples are independent, and the distribution of DPR Scores follows normal distribution. Group DPR Score Treated 24 Treated 43 Treated 58 Treated 71 Treated 43 Treated 49 Treated 61 Treated 44 Treated 67 Treated 49 Treated 53 Treated 56 Treated 59 Treated 52 Treated 62 Treated 54 Treated 57 Treated 33 Treated 46 Treated 43 Treated 57 Control 42 Control 43 Control 55 Control 26 Control 62 Control 37 Control 33 Control 41 Control 19 Control 54 Control 20 Control 85 Control 46 Control 10 Control 17 Control 60 Control 53 Control 42 Control 37 Control 42 Control 55 Control 28 Control 48 Math 140 Project Steps: 1. Before doing any statistical analysis or looking carefully at the values in your data, ponder what the data might show and develop one interesting hypotheses that you will evaluate in your project. For example, suppose your data gives the diameters for samples of two different kinds of trees, perhaps two species of rubber trees in a tropical rain forest. Suppose one kind grows in shadier locations and the other grows in sunnier locations. You might speculate that the species that grows in sunnier locations tends to be larger than the other species. More specifically, you could make a hypothesis that the mean diameter of all the rubber trees in the species that grows in sunny conditions is larger than the mean diameter of all the rubber trees in the species that grows in shady conditions. 2. As you have learned, there are several ways to display data on quantitative variables graphically. Input your data into StatCrunch. Then choose and produce at least two types of graphical displays that are appropriate for your data. Summarize the key features of each distribution, and then discuss how the two distributions compare. Discuss the extent to which this comparison supports the hypothesis you made in part 1. 3. Please answer the indicated questions below: 1. Did your data come from an experiment or observational study? 2. Identify the observational/experimental units. 3. What is your response variable? 4. What is your explanatory variable? 5. Was random assignment used? 6. Was the experiment blind? Double-blind? 7. Suggest some lurking variables that could confound any cause and effect conclusions that you would ultimately like to draw from your study. 8. Describe a modification of the study design that could control for at least one of these possible lurking variables. 4. Do your data come from random samples of populations? Identify the populations involved. As you have learned, the inferential methods (confidence intervals and tests) on quantitative methods that you are learning in this class depend on the assumption that your data are from a population in which the variable involved is at least approximately normally distributed. Based on the graphical displays you made in part 1, are the data approximately bell-shaped? 5. In part 1 of this project you developed one hypothesis that you would evaluate in your project. In this phase you will define the populations of interest and the parameters that pertain to your analysis, and then you will estimate your parameter(s). Here is an example to show how to define your populations and parameters: Suppose that your data gives the diameters for samples of two different species of rubber trees that grow in a tropical rain forest. One kind grows in shadier locations and the other grows in sunnier locations. Suppose that in part 1 you made the hypothesis that the species that grows in sunnier locations tends to be larger that the species that grows in shadier locations. Specifically, you may then hypothesize that the mean diameter of all the rubber trees in the species that grows in sunny conditions is larger than the mean diameter of all the rubber trees in the species that grows in shady conditions. Then your populations are: Population1: All trees in the species that grows in sunnier conditions Population 2: All trees in the species that grows in shadier conditions and your parameters are: mean diameter of all trees in the species that grows in sunnier conditions mean diameter of all trees in the species that grows in shadier conditions 1. Define your populations of interest (Population 1 and Population2) 2. Define your population parameters (Parameter 1 and Parameter 2). Make sure to use symbols as well as words. 3. Give a point estimate (statistic) of each parameter. 4. Give an interval estimate of each parameter. Show your work, and use a 95% level of confidence. 5. Give a clear and in context interpretation of what each of your confidence intervals says. 6. In this part you will use the formal methods of statistical inference to assess your hypotheses through comparisons. 1. (a) Find a confidence interval for the difference between the two parameters (means) that you analyzed individually in part 5. Use 95% level of confidence. (b) Give a clear, in-context interpretation your confidence interval. 2. (a) Use a hypothesis test to test whether the difference between your means is zero, against an alternative appropriate to the original hypothesis you made in part 1 of this project. Choose a significance level before calculating the test statistic, and be sure to report it. (b) Give a clear, in-context conclusion based on the results of (a). Do not just say "We reject the hypothesis..." or "We do not reject the hypothesis...", rather, indicate the strength of the evidence supporting your original hypothesis from part 1. 3. Are the results of #1 and #2 reasonably consistent with each other in terms of whether they support or tend to refute your original hypothesis? Discuss this briefly.

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