Question: Part 4 : Linear Regression Model In this part, we will create our linear regression model by calculating the model coefficients hat ( ) 0

Part 4: Linear Regression Model
In this part, we will create our linear regression model by calculating the model coefficients hat()0 and hat()1. Before we can do so,
we have one last quantity to calculate, which we will denote by SxY. The formula for this value is provided below.
SxY=i=1n(xi-(x))(yi-(?bar(y)))=(x1-(x))(y1-(?bar(y)))+(x2-(x))(y2-(?bar(y)))+cdots+(xn-(x))(yn-(?bar(y)))
Create a markdown cell with a level 2 header that reads "Part 4: Linear Regression Model".
In the same cell, add unformatted text explaining that in this part we will calculate SxY, which we will then use to find the
coefficients for our linear regression model.
Calculate SxY, storing the result in a variable named Sxy. You will need to use a loop to perform this task. For the sake of
efficient memory usage, you should not create any additional lists when performing this calculation.
Print the result with text output as shown below. Round the displayed value of Sxy to 2 decimal places. Do not round
the actual values stored within the variables themselves, just the values displayed.
Sxy=
We are now ready to calculate the model coefficients hat()0 and hat()1 using values that we have previously calculated. Formulas
for these coefficients are provided below.
hat()1=SxYsxx and hat()0?b=ar(y)-hat()1*x
Create a markdown cell with unformatted text explaining that we will now be calculating the coefficients of our model.
Calculate the values of hat()0 and hat()1 storing the results in variables named beta_ and beta_1. Print the results with text
output as shown below. Round the displayed value of beta_ to 4 decimal places and round the displayed value of
beta_1 to 8 decimal places. Do not round the actual values stored within the variables themselves, just the values
displayed.
beta0=
beta1=xxxx
 Part 4: Linear Regression Model In this part, we will create

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