Weekly data collected on a particular beverage brand used the price of beverage to predict the number of units sold. A simple linear regression model is given as y=2259-1418x. The ANOVA F test p-value=0.000, and r 2 = .597. Which is the best interpretation of the slope of the line
Group of answer choices
As the price increasess by 1 dollar, sales will increase on average by 2259
As the price increases by 1 dollar, sales will decrease, on average by 1418
As the sales increase by 1 unit, the price will increase, on average by 2259 dollars
As the sales increase by 1 unit, the price will decrease, on average by 1418
Slope =-1418 (Negative value)
As the price increases by 1 dollar, sales will decrease, on average by 1418
Weekly data collected on a particular beverage brand used the price of beverage to predict the...
Supermarkets can use the scanning data collected at the checkout counters to evaluate the effect of price on the sales of any product. Weekly data was collected on a particular beverage brand, including sales (in number of units) and price (in dollars). Based on a simple linear regression analysis, the fitted regression equation was: Y = 2259 - 1418 X. The ANOVA F-statistic was 60.52 with the p-value of <0.0001, and R2 = 0.597. According to this model, is the explanatory...
A linear model was fit to predict weekly Sales of frozen pizza (in pounds) from the average Price ($/unit) charged by a sample of stores in a city in 39 weeks over a three-year period. The average Sales were 61,802 pounds (SD=10,070 pounds), and the correlation between Price and Sales was −0.535. If the Price in a particular week was two SD higher than the mean Price, how much pizza would you predict was sold that week?
To predict the price of a home in Ulster County, NY data on the following factors (number of bathrooms, the square footage of the house, and the age of the house (yrs) were collected. A regression analysis is given below. ANOVA df SS MS F Regression 3 899875 299958.4 Residual 24 151882 6328.4 Total 27 1051757 P-value Intercept 0.004 Bathrooms 0.995 Sq. ft. 0.000 Age (yrs) 0.040 Name the variables that are influential at the 0.05 level. The following questions...
Could you teach me do this by Ti83or 84?
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPT) and the cost of a slice of pizza We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice 0.15 0.35 1.00 1.25...
1. A sample of 33 companies was randomly
selected and data collected on the average annual
bonus ($), turnover rate (%), and trust index (measured on a
scale of 0 — 100). The regression
equation is TurnoverRate = 12.1005 -0.07149TrustIndex
-0.0007216AverageBonus. The correct
interpretation for the coefficient of Averager Bonus is
A) After accounting for Trust Index, an increase of $10,000 in
annual bonus is associated with a
decrease of 7.216% in turnover rate.
B) After accounting for Trust Index,...
A team of researchers in Economics are investigating the relation between annual income and weekly savings of families. It is supposed that the higher the income, the more will be the predisposition of a family to save money, with savings and income linked through a linear relationship. The team collected data for a sample of 157 families, recording the overall annual income (in 1000 of euros) and the average weekly savings (in euro) over a period of one year. The...
The manufacturer of a light fixture believes that the dollars spent on advertising, the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales. The manufacturer randomly selects 10 months and performs a regression analysis - part of the output appears below. The sales are in thousands of units per month, the advertising is given in hundreds of dollars per month, the price is the unit retail price...
just answer multiple choice
5E) Which one of the statement A-E is the correct interpretation
of the Y-intercept?
There is no practical interpretation since one cannot have zero
years of sales.
The model predicts that the annual sale is $161.3855 when their
years of experience are zero.
The model predicts an increase of annual sale of $161.3855 if
the price goes up by $1.
The model predicts an increase in annual sales of $11369.4 if
the price goes up by...
A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model, y=β0+β1x, where y=appraised value of the house (in $thousands) and x=number of rooms. Using data collected for a sample of...
Consider the following results of a multiple regression model of dollar price of unleaded gas (dependent variable) and a set of independent variables: price of crude oil, value of S&P500, price U.S. Dollars against Euros, personal disposal income (in million of dollars) : Coefficient t-statistics Intercept 0.5871 68.90 Crude Oil 0.0651 32.89 S&P 500 -0.0020 18.09 Price of $ -0.0415 14.20 PDI 0.0001 17.32 R-Square = 97% What will be forecasted price of unleaded gas if the value of independent...