Application of Normal Probability Distributions in Making PredictionsProbability is used to model uncertainty in real-world measurements. Statistics uses probability to quantify the accuracy in the analysis of data. Module One covered discrete and continuous probability distributions and their properties. This module focuses on a specific continuous distribution—the normal distribution—and how it can be used to make decisions and predictions. Additionally, this module will introduce students to the central limit theorem and students will learn how to apply this theorem to sample proportions and sample means.Complete the Module Two problem set in MyStatLab (14 questions). See Instructor Tips in MyStatLab for video solutions for select problems. In the Module Two problem set, video solutions are available for problem numbers 4, 5, 8, 10, and 12.Click on the MyStatLab link on the left-side navigation to access this resource. You are allowed unlimited attempts to complete this assignment.

Conduct an analysis and hypothesis test of your choice on the data you collected. Write a 250-500 word research summary of the findings generated in the assignments for Topics 2 through 5. The research summary should address the following. Explain what type of analysis and hypothesis test was conducted on the data collected. Summarize the survey results based on the results of the data you analyzed. Include the Excel analysis as part of the document. APA format is not required, but solid academic writing is expected. This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

The half-life of cesium-137 is 30 years. Suppose we have a 17-g sample.(b) Find a function m(t) = m0e−rt that models the mass remaining after t years. (Round your r value to four decimal places.) m(t) =