Help & explain please Regression 1. A researcher is willing to investigate whether there is any...
Simple Linear regression 1. A researcher uses a simple linear regression to measure the relationship between the monthly salary (Salary measured in dollars) of data scientists and the number of years since being awarded a Master degree (Master Degree). A random sample of 80 observations was collected for the analysis. A researcher used the econometric model which has the following specification Salary,-β0 + β, Master-Degree, + εί, where i = 1, , 80 The (incomplete) Excel output of equation (1)...
6 A market manager condacted a study to determine whether there is a linear relatioreship betwecn money spent and advertising and company sales. Determine if there is a linear correlation or not. Uise a-0.05 Advertising Expnscs 24 1.6 2.0 2.6 14 16 20 22 Company184 Sales 225 184 220 240 180 184 186 215 (Each one times $1000) Find: a) The correlation coefficient r b) In your opinion, is there a strong linear correlation? Weak lincar correlation? Explain c) What...
Please help me solve 43-45 43. Use the regression equation below to predict the profits for the restaurant when the population size is 14.8 thousand people. (Plug in 14.8 for X in the equation and calculate Y) Regression Line: Y--30.3091+6.0211 X 44. (True or False?) This correlation study proves that more people in a city will cause the restaurant profits to increase (True or False?) It will be fine to use the regression equation to predict the profits for the...
The CFO of the company would like to use the number of years employees have been with the company to predict the employees’ salaries. To that end, the CFO decided to fit the linear regression model E(y) = β0 + β1x, where Y = the salary of an employee (in thousands of dollars) and X = the years employed with the company. Using data collected for a sample of n = 35 employees of the company, the following result was...
Regression 1 You are interested in an association between age and gum recession (measured as the average over all surfaces for a patient) You measured data from 5 patients Age (years) Recession (mm)( - }* (y _ ¥)* (x-(y-g) 3 0.8 400 1.44 24 1.2 225 0.64 12 20 2.2 0.04 -0.6 27 1.9 16 0.01 -0.4 64.6 57 3.9 1156 3.61 Note that the average age is 23 years and average gum recession is 2. You want to see...
Please explain in detail and provide answers Linear Regression & Correlation Coefficient Practice Would you consider the data to be accurate, precise or both? Justify. 1. 10 T 2. The table below shows the percentage of females in the U.S. labor force at various times throughout history Years after 1900 | 50 Percentage | 60 T70- T80-T90 8.1 42.5 45.3 100 52.0 Enter the data into your calculator or excel and give the equation. Round slope & y-intercept to 2...
Question 9 (1 point) You work for a company in the marketing department. Your manager has tasked you with forecasting sales by month for the next year. You notice that over the past 12 months sales have consistently gone up in a linear fashion, so you decide to run a regression the company's sales history. You find that the regression equation for the data is (sales) 104.21*(time) + 113.38. In 11 months you see the actual sales quantity was 380.64....
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
Please answer today! I will upvote/rate. Best fitting line. Matrix. 5. Predicting Populatioin The data below records the population of Irvine, CA (in thousands of people) for the years 2010-2016: Year Population 220 2010 229 2011 2012 236 2013 247 2014 256 2015 266 2016 277 Suppose we want to use this data to predict the population in future years. (a) To use the year as a predictor variable, encode 2010 as 1, 2011 as 2, 2012 as 3, etc....
actually other expert help me with a solution for hw1 (thanks a lot for him). so , if you look just the question that I post you can see it or just write the first line of the question , thank you for your interest in my question . I post the code that I used at first homework # Set directory to data folder setwd("C:data") # getwd() # Read data from csv file data <- read.csv("SweetPotatoFirmness.csv",header=TRUE, sep=",") head(data) str(data)...