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Question: Divide. (6x^2+27x+8)/(x+4). Your answer should give the quotient and the remainder Answer: (6x^2+27x+8)/(x+4) Written as Step 1: 𝑥 + 4) 6x2+27x+8 ( 6x 1) First check to get 6x2, on 6x2+ 24x multiplication with x; (x * 6x = 6x2 ) 0 + 3x + 8 that is 6x, so multiple with 6x Step 2 ...
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For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You will examine each scenario, choose a categorical data analysis and run a sample test.To prepare for this Assignment:Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

Case Study Assignment

We will work with the data for homes for sale in Lafayette and West Lafayette, Indiana. The response (dependent) variable ...

Case Study Assignment

We will work with the data for homes for sale in Lafayette and West Lafayette, Indiana. The response (dependent) variable is Price, the asking price of a home. The data set contains the following explanatory (independent) variables: SqFt, the number of square feet for the home Bedrooms, the number of bedrooms Baths, the number of bathrooms Garage, the number of cars that can fit in the garage The data set contains 44 homes for sale in zip code 47904. a few homes have prices that are somewhat high relative to the others. Similarly, some values for SqFt are relatively high. Exclude any home with Price greater than $150,000 and any home with SqFt greater than 1800 ft2. After excluding process, how many houses do you have in the data set? (20 p) Regress price (dependent variable) on square feet (independent variable) and write the regression equation. (18 p) a. What proportion of the variance in Price variable can be explained by the Square Feet variable? b. Is this proportion of variance statistically significant at .05 level of significance? Justify your answer. c. Does Square feet significantly predict the price of the house? Justify your answer. Recode the “Bedrooms” categorical variable to be Bed3 = 1 if the home has three or more bedrooms and Bed3 = 0 if it does not. Bed3 is called as Dummy variable (indicator variable). (36 p) Run the regression analysis including the variables of price and the dummy variable, Bed3 and write the regression equation. What proportion of variance in the price of the house can be explained by the number of bedrooms of the house? Is this proportion of variance statistically significant at .05 level of significance? Justify your answer. Does number of bedrooms significantly predict the price of the house? Justify your answer. What is the predicted price for homes with two or fewer bedrooms (Bed3 = 0)? What is the predicted price for homes with three or more bedrooms (Bed3 =1)There are 3 more questions. Bringing it to a total of 6Follow directions on assignment and display the work.PLEASE READ: I included extra documents labeled "HELP" in the beginning of their title to help guide you through the assignment that the instructor provided. It is similar to assignment and designed to help understand it. It is there for your reference and not necessary to use. The Case Study Data for Assignment #7 excel document and Assignment 7_Case Study_FIn330 pdf file are the only two needed to complete the assignmentThe rest are there for reference and any help.

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2 pages

1. Consider the curves y=2√x and y=x and the region R bounded by both curves in the first b. Find the volume of the soli ...

1. Consider the curves y=2√x and y=x and the region R bounded by both curves in the first b. Find the volume of the solid obtained by rotating R ...

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Find the probability of the result using the normal curve approximation to the binomial distribution. A 25-question multip ...

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For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You ...

Testing for Bivariate Categorical Analysis

For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You will examine each scenario, choose a categorical data analysis and run a sample test.To prepare for this Assignment:Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

Case Study Assignment

We will work with the data for homes for sale in Lafayette and West Lafayette, Indiana. The response (dependent) variable ...

Case Study Assignment

We will work with the data for homes for sale in Lafayette and West Lafayette, Indiana. The response (dependent) variable is Price, the asking price of a home. The data set contains the following explanatory (independent) variables: SqFt, the number of square feet for the home Bedrooms, the number of bedrooms Baths, the number of bathrooms Garage, the number of cars that can fit in the garage The data set contains 44 homes for sale in zip code 47904. a few homes have prices that are somewhat high relative to the others. Similarly, some values for SqFt are relatively high. Exclude any home with Price greater than $150,000 and any home with SqFt greater than 1800 ft2. After excluding process, how many houses do you have in the data set? (20 p) Regress price (dependent variable) on square feet (independent variable) and write the regression equation. (18 p) a. What proportion of the variance in Price variable can be explained by the Square Feet variable? b. Is this proportion of variance statistically significant at .05 level of significance? Justify your answer. c. Does Square feet significantly predict the price of the house? Justify your answer. Recode the “Bedrooms” categorical variable to be Bed3 = 1 if the home has three or more bedrooms and Bed3 = 0 if it does not. Bed3 is called as Dummy variable (indicator variable). (36 p) Run the regression analysis including the variables of price and the dummy variable, Bed3 and write the regression equation. What proportion of variance in the price of the house can be explained by the number of bedrooms of the house? Is this proportion of variance statistically significant at .05 level of significance? Justify your answer. Does number of bedrooms significantly predict the price of the house? Justify your answer. What is the predicted price for homes with two or fewer bedrooms (Bed3 = 0)? What is the predicted price for homes with three or more bedrooms (Bed3 =1)There are 3 more questions. Bringing it to a total of 6Follow directions on assignment and display the work.PLEASE READ: I included extra documents labeled "HELP" in the beginning of their title to help guide you through the assignment that the instructor provided. It is similar to assignment and designed to help understand it. It is there for your reference and not necessary to use. The Case Study Data for Assignment #7 excel document and Assignment 7_Case Study_FIn330 pdf file are the only two needed to complete the assignmentThe rest are there for reference and any help.

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Statistics Question