1. Michael Abramson Raphal Bils Lucie Wullschleger Business ForecastingDoes Junk Food make you feel better?People tend to eat more and more Junk Food. Does the level of happiness is related with the junk foodsales worldwide? Is Junk Food related to well-being? CountriesLevel of happiness (X)Junk Food Sales (Y) $ Russia32 180,000.00 $ Spain 36 220,000.00 $ Brazil71 390,000.00 $ Canada65 510,000.00 $ China 78 890,000.00 $ United Kingdom85 1,300,000.00 $ United States 88 1,450,000.00 $ Japan 92 1,340,000.00 $ South Korea 82 830,000.00 $ Germany 73 610,000.00 $ France46 290,000.00 $ Tawan37 490,000.00SUMMARY OUTPUT Regression StatisticsMultiple R 0.858003R Square0.736169Adjusted RSquare 0.709786StandardError242969.1

2. Michael Abramson Raphal Bils Lucie Wullschleger Business ForecastingObservations 12ANOVA SignificanDf SS MS Fce F1.65E+1Regression11.65E+12 2 27.90302 0.000356Residual 10 5.9E+11 5.9E+10Total112.24E+12CoefficienStandardLower Upper Lower Upper ts Errort Stat P-value95% 95%95.0% 95.0%-Intercept-446134 229531.7 1.94367 0.080589-957563 65294.18-95756365294.18X Variable 117647.91 3340.933 5.28233 0.000356 10203.85 25091.97 10203.8525091.97Null Hypothesis H0: The amount of the junk food sales will not be statistically significant and dependenton the change in level of happiness.Alternative Hypothesis: H1: The amount of our sales will be affected in a statistically significant mannerby the level of happiness.Sales vs. Happiness Level Example for Regression and Interpreting the Statistics:The goal of regression is to produce an equation that "best" depicts the relationship and minimizes thedeviations between the plotted points.A "tighter" the regression line, the better Level of Happiness (X) Junk Food Sales (Y) 1001,600,000.001,400,000.00801,200,000.001,000,000.0060800,000.0040600,000.00400,000.0020200,000.00 - 0 United Kingdom CanadaFrance RussiaBrazil China United States JapanTawanSpain Germany South Korea Brazil ChinaFrance SpainCanadaSouth KoreaRussiaUnited StatesJapan Tawan United KingdomGermanyWhat is the Data Telling You? 3. Michael Abramson Raphal Bils Lucie Wullschleger Business ForecastingThe collection of data for tracking is best when its been tracked over a longer period of time or a surveyhas been done with a fairly high sample size and limited questioning bias.The R squared value tells us what percent of the variation in the data is explained by the regressionequation given.The Regression equation for a line is: Y = mX + bThe Least Square line equation is: Y = b0 + b1XThe R squared value of 73.6% tells us what percent of the variation in the data is explained by theregression equation given.This is high and seems to show a positive linear correlation between happiness level and sales.In a boarder sense, an R squared of .30 could be considered high when forecasting the economybecause of multiple input variables. Example, the weather make you more or less happy, the stress youhave in your city, the revenue per capita in your countryThe T statistic will help us determine if the regression equation is a good one to use for forecasting.The T statistic is an independent test that reveals if an X variable has a statistically significant effect onthe Y (stress levelvs sales).It is calculated by dividing the X coefficient by the standard error.The T statistic is used because its possible to create a model with more than 1 variable (multipleregression) and as the number of variables is added, the R squared will rise.The general rule for significance of our T statistic is > 2 for a positivecorrelation or < -2 for a negativecorrelation.When considering if a model is a good forecaster, its best to have both a high R squared and T statistic(>2 or < -2)The Standard Error is synonymous with the standard deviation, which means how far something willmove from the mean or center of the curve.The standard error is an estimate of the amount of variability inherent in the regression and can bemeasured with the MSE or Mean Square ErrorThe best forecast would have a lower standard deviation, which is associated with less risk.The P Value is the probability of accepting the null hypothesis (our general assumption that stress levelhas no affect on sales of ice cream) when testing at certain confidence levels: 90%, 95%, 99%.In this case, its associated with the independent variable and is usually good if its < .05 or