Situation: The Ipod Touch has been out for many years now and a lot of data has been collected.Relevant Relationship:There is a functional relationship between Price of an IPod Touch,𝑝 and Weekly Demand,𝑠.Below is a table of data that have been collectedPrice,𝑝,($) Weekly Demand,𝑠,(1,000s)150 208170 199190 200210 184230 182250 176A. Find the linear model that best fits this data using regression and enter the model below(for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1)𝑠=  B. The squared correlation coefficient was 0.95(note: values less than 0.95 MAY mean the model is not appropriate for making predictions)Now answer these two questions using the UNROUNDED model parametersC. What does the model predict will be the weekly demand if the price of an ipod touch is $246 ? (nearest 100)D. According to the model at what should the price be set in order to have a weekly demand of 179,800 ipod Touches? $ (nearest $1)

The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries.grams Vitamin Ccontent in mg50 9.460 13.970 18.380 22.890 27100 31.7110 37.2A)  Find the regression equation:     𝑦= 𝑥+   Round your answers to 3 decimal places B)  Answer the following questions using your un-rounded regression equation.  If we test 140 grams of raspberries what is the expected Vitamin C content?   𝑚𝑔 (round to the nearest tenth)

A simple linear regression model was run to understand the relationship between:price in thousands of dollars (P)sales in dollars (S)The model output the following equation:S = 50,000 – 8P Which of the following is true about the relationship between sales and price?An increase of $1 in price is associated with a decrease of $8,000 in salesAn increase of $1 in price is associated with a decrease of $80 in salesAn increase of $1 in price is associated with a decrease of $42,000 in salesAn increase of $8 in price is associated with an increase of $8,000 in sales

The following table shows actual and projected worldwide annual sales and average selling prices of a certain type of smartphone in 2020 and 2024.Year 2020 2024Selling Price ($) 550 350Sales (millions) 210 770(a)Use the data to obtain a linear demand function for this type of cell phone. (Let p be the price, and let q be the demand).q(p) = Use your demand equation to predict sales (in millions) if the price is lowered to $300. million phones(b)Fill in the blank.For every $1 increase in price, sales of this type of cell phone decrease by million units.

Select all the tasks where linear regression algorithm can be applied.Note: Multiple options can be correct.You have a data set of BMI (body mass index) and fat percentage of the customers of a fitness centre. The fitness centre wants to predict the fat percentage of a new customer, given his BMI.You have collected data from a house rental website like commonfloor.com. The data includes the rental prices of apartments and customer ratings as HIGH or LOW. You want to predict the customer rating, given the rental price of a new house.You want to predict the sales of a retail store based on its size, given the data set of sales of retail stores and their sizes.You want to predict whether a customer is likely to leave the telecom network.

Question 41 ptsUse the data given below to answer the following question(s).Following is an extract from the database of a construction company. The table shows the heightof walls in feet and the cost of raising them. The estimated simple linear regression equation isgiven as Ŷ = b0 + b1X. (Hint: Use Excel functions).What is the estimated cost of raising a 10-inch wall?Group of answer choices1505.7861103.578968.61091123.008