Part 2 Exploratory Data Analysis 200 points 1 Categorica.pdf

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Part 2: Exploratory Data Analysis (200 points) 1. Categorical data: For 4 of the categorical variables in the dataset, create a pie chart or bar graph showing the distribution of values. Include screenshots or images of the graphs. For each of these graphs, write 1-2 sentences describing the distribution of data. The sentences explaining the graphs should describe the distribution you see, e.g. which values come up most often, which values come up least often, and any other interesting details. 2. Quantitative data: For 4 of the quantitative variables in the dataset, create a histogram, stem and leaf plot, or boxplot showing the distribution of values. Include screenshots or images of the graphs. Also include the five number summary for each quantitative variable. For each of these graphs, write 1-2 sentences describing the distribution of data. Question 3 continues on the next page.

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Most retailers wish they knew more about their sales and customers' buying habits. They want to know the right levers to push and pull to increase sales and customer satisfaction. However, there are many obstacles in their way that keep them from these insights. It could be that their data is split between disconnected systems or that they are dealing with legacy systems that can't keep up. It's complicated to converge the sales from different online and offline sales channels for analysis. Centralized the location and using the Data Cube gives benefits for business such as knowing the sales trends by product type, region, or time period and knowing how much inventory you have of each product easily. This proposed system will discuss what capabilities need to perform sales trend analysis and contribute the sales trend analysis effectively by using Data Cube in viewing data. Myint Myint Yee | San San New | Myat Mon Kyaw "Effective Data Viewing in Sale Trend Analysis by using Data Cube" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27836.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-miining/27836/effective-data-viewing-in-sale-trend-analysis-by-using-data-cube/myint-myint-yee

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ECON 3406 Multiple Regression Instructions LO2.2 In this assignment, you are provided with data from a research paper by Ella Hartenian and Nicholas Horton, who examined whether or not there was a relationship between rail trails and property values in Northampton, MA. The data are located in the file ‘house prices.xlsx’ which is in your e-mail on D2L. Please see the accompanying word document, ‘documentation.docx,’ which describes what each of the columns in the data set mean and how they are scaled. For this assignment you will learn how to estimate a common regression model used in economics, finance, and real estate called a “hedonic price model.” 1. Create a copy of the data set by right-clicking the tab at the bottom and clicking ‘Move or Copy...’, then create another copy of the data set in the same workbook. Label this copy “Regression 1” and the original tab “Original Data.” Now click on the tab for “Regression 1.” Delete all variables except ‘price2014,’ ‘bedrooms,’ ‘garage space’, ‘nofullbath’, ‘norooms’, ‘squarefeet,’ and ‘walkscore.’ You should have seven total variables. Make sure ‘price 2014’ is the far left variable, then estimate the model where ‘price2014’ is a function of the other six variables. Then answer the questions: (a) For each variable, explain what the sign of the regression coefficient is, what the magnitude is (i.e., if x goes up by one unit how much does y increase by), and whether or not the results of your regression are consistent with what you believed the sign and magnitude to be. Then explain if any variables are insignificant. • Use p < 0.1 as the p-value cutoff for whether results are significant. (b) Write down the equation of your regression line, including all variables. Next, calculate the average value for each of your six explanatory variables using the AVERAGE() function in Excel. Finally, make a prediction for the price if each of the variables take their average value. (c) Explain briefly if there are any variables in the data set you think should have been included and, if so, why. You must refer to at least one other variable. IMPORTANT: TYPE YOUR ANSWERS IN A TEXT BOX (“INSERT” A TEXT BOX). MAKE SURE TO ADDRESS EACH QUESTION (a, b, and c) LO2.3 In this assignment you are provided with data from a research paper by Ella Hartenian and Nicholas Horton, who examined whether or not there was a relationship between rail trails and property values in Northamp- ton, MA. The data are located in the file ‘house prices.xlsx’ (same data used above) which is in your e-mail on D2L. Please see the accompanying word document, ‘documentation.docx,’ which describes what each of the columns in the data set mean and how they are scaled. For this assignment you will assess whether rail trails influence property values. 1. Create a copy of the same data set used for “LO2.2” by right-clicking the tab at the bottom and clicking ‘Move or Copy...’, then create another copy of the data set in ...

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1. Part 2: Exploratory Data Analysis (200 points) 1. Categorical data: For 4 of the categorical variables in the dataset, create a pie chart or bar graph showing the distribution of values. Include screenshots or images of the graphs. For each of these graphs, write 1-2 sentences describing the distribution of data. The sentences explaining the graphs should describe the distribution you see, e.g. which values come up most often, which values come up least often, and any other interesting details. 2. Quantitative data: For 4 of the quantitative variables in the dataset, create a histogram, stem and leaf plot, or boxplot showing the distribution of values. Include screenshots or images of the graphs. Also include the five number summary for each quantitative variable. For each of these graphs, write 1-2 sentences describing the distribution of data. Question 3 continues on the next page

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