The purpose of this assignment is to solve business problems using linear optimization techniques and interpret the results to determine optimal solutions for business problems.Using specified data files, chapter example files, and templates from the “Topic 5 Student Data, Template, and Example Files” topic material, complete Chapter 14, Problems 79 (part a), 80 (part a), 81, 86 (part a), and 89 from the textbook. Use Microsoft Excel’s Solver Add-In to complete these problems. For all problems except 89, run the Solver’s Answer and Sensitivity Reports. Interpret and summarize the key results.To receive full credit on the assignment, complete the following.Ensure that all Solver settings are defined through the use of the Solver dialog box.Ensure that Excel files include the associated cell functions and/or formulas if functions and/or formulas are used.Include a written response to all narrative questions presented in the problem by placing it in the associated Excel file.Include Answer and Sensitivity Reports interpretation and summary of key results.Place each problem in its own Excel file

CENTRAL TENDENCYDownload and save the Week 3: Central Tendency [DOCX] document.Complete the assignment within the Word document, and submit it to your instructor by Sunday, 11:59 p.m. central time.SCORING GUIDEYour Work will be evaluated using this criteria.VIEW SCORING GUIDECompetencies MeasuredBy successfully completing this assignment, you will demonstrate your proficiency in the following course competencies and assignment criteria:Competency 1: Apply appropriate notation, terminology, procedures, and concepts to statistics problems.Describe a distribution.Calculate measures of variability in Excel from a group of raw scores.Calculate measure of variability in SPSS from a group of raw scores.Clean data.Import data to SPSS.Competency 2: Form logical conclusions about real-world problems through descriptive and inferential statistical procedures.Interpret means in a chart.Interpret standard deviations in a chart.

Math 140 Project: Exploring relationships between two variables In this project, you will search two quantitative variables that may have a linear correlation. You will describe and analyze the relationship between the variables the way it is explained in Chapter 4 (4.1-4.2). You will, then, create a written report including all 4 parts below and turn in by the stated due date according to the guidelines provided in this paper. Required components:1. Understand the Problema) Search for two quantitative variables that may have a linear correlation from the internet, in Canvas or any other media. You may also get the data by surveying 15-20 people. Possible websites to look for data: You may obtain the data in StatCrunch.com: Click explore and click Data. http://www.city-data.com/ for demographic information about cities http://www.cde.ca.gov/ta/ac/ap/ for academic performance index. http://graphics.latimes.com/responsivemap-pollutio... for pollution burdens. Website where you found the data: b) Use your intuition and/or experience to predict and write down the descriptions of the possible relationship: Form, Direction, Strength, and outlier, etc. c) Develop a question that address a possible linear correlation between two variables. State the question(s):Identify two variables from the data that are relevant to answer the questions: 2. Analyze the paired Dataa) What is the likely explanatory variable in the paired data?b) Draw a scatter plot of the data. Does the graph show a linear relationship between the variables? Comment on the direction and strength appeared on the scatter diagram.c) Compute the linear correlation coefficient between the two variables and interpret the meaning specifically for your data. d) Find the equation of the least-squares regression line.e) Interpret the slope and y-intercept, if appropriate. f) Use the equation of the least-squares regression line to predict the outcome (y-value) for one of the x-values in your data.g) Find the residual for the x-value you chose in part (f). Explain what it means when a residual is positive or negative.3. Draw Conclusions a) What do the results indicate about the relationship between two variables? b) Do you think there is a causal relation between the variables? Explain. c) Relate the comments you made in step 1b before analyzing the data by commenting on both of the following: How your expectation differs (or do not differ) from the actual results? If it is relevant or meaningful in context, think of a way that these results could be used in practice.4. Summarize Write a short summary of the main findings that you discovered. Math 140 Project: Exploring relationships between two variables -Score Sheet (Total 50 points)Name:________________________________________ Date:__________________________________Title of the project: ____________________________________________________________________Website where you found the data:_______________________________________________________Project Grade: __________________________________