Chapter 8.1, Problem 12BSC

For each of the time​ series, construct a line chart of the data and identify the characteristics of the time series​ (that is,​ random, stationary,​ trend, seasonal, or​ cyclical). Month    PercentApr 1972    4.97May 1972    5.00Jun 1972    5.04Jul 1972    5.25Aug 1972    5.27Sep 1972    5.50Oct 1972    5.73Nov 1972    5.75Dec 1972    5.79Jan 1973    6.00Feb 1973    6.02Mar 1973    6.30Apr 1973    6.61May 1973    7.01Jun 1973    7.49Jul 1973    8.30Aug 1973    9.23Sep 1973    9.86Oct 1973    9.94Nov 1973    9.75Dec 1973    9.75Jan 1974    9.73Feb 1974    9.21Mar 1974    8.85Apr 1974    10.02May 1974    11.25Jun 1974    11.54Jul 1974    11.97Aug 1974    12.00Sep 1974    12.00Oct 1974    11.68Nov 1974    10.83Dec 1974    10.50Jan 1975    10.05Feb 1975    8.96Mar 1975    7.93Apr 1975    7.50May 1975    7.40Jun 1975    7.07Jul 1975    7.15Aug 1975    7.66Sep 1975    7.88Oct 1975    7.96Nov 1975    7.53Dec 1975    7.26Jan 1976    7.00Feb 1976    6.75Mar 1976    6.75Apr 1976    6.75May 1976…

Hi, I need to make sure I have drafted a thorough analysis, so please answer the following questions. Based on the data in the attached image, develop a regression model to forecast the average sales of football magazines for each of the seven home games in the upcoming season (Year 10). That is, you should construct a single regression model and use it to estimate the average demand for the seven home games in Year 10. In addition to the variables provided, you may create new variables based on these variables or based on observations of your analysis. Be sure to provide a thorough analysis of your final model (residual diagnostics) and provide assessments of its accuracy. What insights are available based on your regression model?

I want to make sure that I included all possible variables and observations. There is a considerable amount of data in the images below, but not all of it may be useful for your purposes. Are there variables contained in the file that you would exclude from a forecast model to determine football magazine sales in Year 10? If so, why? Are there particular observations of football magazine sales from previous years that you would exclude from your forecasting model? If so, why?

Stat questions

1) and let Xt is stochastic process with WSS and Rxlt t+t) 1) E (X5) = \ 1 2 Show that E (X5 = X 3 = 2 (= = =) Since X is WSSEL 2 3) find E(X5+ X3)² 4) sind E(X5+X2) J=1 ***

Prove that 1) | RxX (T) | << = (R₁ " + R$) 2) find Laplalse trans. of Normal dis: 3) Prove thy t /Rx (z) | < | Rx (0)\ 4) show that evary algebra is algebra or not.

For each of the time​ series, construct a line chart of the data and identify the characteristics of the time series​ (that is,​ random, stationary,​ trend, seasonal, or​ cyclical). Month    Number (Thousands)Dec 1991    65.60Jan 1992    71.60Feb 1992    78.80Mar 1992    111.60Apr 1992    107.60May 1992    115.20Jun 1992    117.80Jul 1992    106.20Aug 1992    109.90Sep 1992    106.00Oct 1992    111.80Nov 1992    84.50Dec 1992    78.60Jan 1993    70.50Feb 1993    74.60Mar 1993    95.50Apr 1993    117.80May 1993    120.90Jun 1993    128.50Jul 1993    115.30Aug 1993    121.80Sep 1993    118.50Oct 1993    123.30Nov 1993    102.30Dec 1993    98.70Jan 1994    76.20Feb 1994    83.50Mar 1994    134.30Apr 1994    137.60May 1994    148.80Jun 1994    136.40Jul 1994    127.80Aug 1994    139.80Sep 1994    130.10Oct 1994    130.60Nov 1994    113.40Dec 1994    98.50Jan 1995    84.50Feb 1995    81.60Mar 1995    103.80Apr 1995    116.90May 1995    130.50Jun 1995    123.40Jul 1995    129.10Aug 1995…

For each of the time​ series, construct a line chart of the data and identify the characteristics of the time series​ (that is,​ random, stationary,​ trend, seasonal, or​ cyclical). Year    Month    Units1    Nov    42,1611    Dec    44,1862    Jan    42,2272    Feb    45,4222    Mar    54,0752    Apr    50,9262    May    53,5722    Jun    54,9202    Jul    54,4492    Aug    56,0792    Sep    52,1772    Oct    50,0872    Nov    48,5132    Dec    49,2783    Jan    48,1343    Feb    54,8873    Mar    61,0643    Apr    53,3503    May    59,4673    Jun    59,3703    Jul    55,0883    Aug    59,3493    Sep    54,4723    Oct    53,164

High Cholesterol: A group of eight individuals with high cholesterol levels were given a new drug that was designed to lower cholesterol levels. Cholesterol levels, in milligrams per deciliter, were measured before and after treatment for each individual, with the following results: Individual Before 1 2 3 4 5 6 7 8 237 282 278 297 243 228 298 269 After 200 208 178 212 174 201 189 185 Part: 0/2 Part 1 of 2 (a) Construct a 99.9% confidence interval for the mean reduction in cholesterol level. Let a represent the cholesterol level before treatment minus the cholesterol level after. Use tables to find the critical value and round the answers to at least one decimal place.