Hi, I am wondering someone to finish this stat homework with writing problem, see the attachment file, and the computer problem using R code , shown as below. then, I will attach the data sets after finishing selected tutor soon.
Computer problems:
We will focus on the daily maximum temperature time series.

First, restrict our data sample to daily data in 2016 and 2017.
Plot out the daily maximum temperature data of the two years. Explain why this time series is not stationary.
The daily maximum temperature data plotted out in Q2 has apparent seasonality. Now, regress daily maximum temperature data on monthly dummies. If you want to formally test whether the time series has seasonality, how would you form your null hypothesis

Plot the fitted outcome values from your regression in Q3 against the true data. Do you think the model fits the data well?
Now let’s further restrict the data sample to daily data in July and August so that the time series would be stationary.
Do you think the daily maximum temperature data for July and August are weakly dependent? Support your conclusion with graphical evidence.
Run an AR(1) model using these two years of July and August daily maximum temperature data. How would you interpret the slope coefficient?
Plot the fitted outcome values from your regression in Q7 against the true data for July and August of 2017.
The fits of regression in Q7 are, of course, only good for the summer months. If we would like to carry out an AR(1) model for the whole time series in 2016 and 2017, how would us modify our AR(1) regression to control for seasonality?
Predict the daily maximum temperature in Jan. 1, 2018 using your AR(1) model in Q9 using R.
First, obtain the daily maximum temperature in Dec. 31, 2017 using R. Then,Predict the daily maximum temperature of Jan. 1, 2018 using your AR(1) model in Q9 BY HAND.

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