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Movie Theatre Attendance Based on Economic Factors Movie Theatre Attendance in By: Madison Kerr Regards to Economic Factors By: Madison Kerr Hypothesis • That movie theatre attendance is not influenced by economic factors. Movie Industry Economy Economic Goods • Two types of goods: – Normal • People buy less of in harsh times – Inferior • People buy more of in harsh times Economic Factors vs Movie Attendance • • • • • • • • • Recession Real GDP per Capita Unemployment Rate Stress Index Consumer Sentiment Velocity of Money S&P 500 Total Public Debt Disposable Personal Income Not Normal Data Probability of Recession Probability Plot of Recession probability Normal - 95% CI 99 Mean StDev N AD P-Value 95 90 Percent 80 70 60 50 40 30 20 10 5 1 -50 -25 0 25 50 Recession probability 75 100 10.06 22.14 17 3.760 <0.005 Not Normal Data Total Public Debt Probability Plot of Total Public Debt (mill) Normal - 95% CI 99 Mean StDev N AD P-Value 95 90 Percent 80 70 60 50 40 30 20 10 5 1 0 5000000 10000000 15000000 Total Public Debt (mill) 20000000 7863564 2982727 17 0.985 0.010 Not Normal Data Stress Index Probability Plot of Stress Index Normal - 95% CI 99 Mean StDev N AD P-Value 95 90 Percent 80 70 60 50 40 30 20 10 5 1 -3 -2 -1 0 Stress Index 1 2 3 0.02688 0.8763 17 0.994 0.010 Not Normal Data Unemployment Rate Normal Data S&P 500 End Values Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Recession probability 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 0 10 20 30 40 50 Recession probability 60 70 80 R sq= 0.1% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Real GDP per Capita 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 40000 42500 45000 Real GDP per Capita 47500 50000 R sq=57% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Unemployment Rate (%) 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 4 5 6 7 8 Unemployment Rate (%) 9 10 R sq=8% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Stress Index 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 -1.0 -0.5 0.0 0.5 1.0 Stress Index 1.5 2.0 2.5 R sq=17.6% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Total Public Debt (mill) 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 5000000 7500000 10000000 12500000 Total Public Debt (mill) 15000000 R sq=26.8% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs SP500 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 500 750 1000 SP500 1250 1500 R sq=43.9% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Velocity of Money 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 1.6 1.7 1.8 1.9 2.0 Velocity of Money 2.1 2.2 R sq=30.2% Parametric vs Non-Parametric Regressions Scatterplot of Tickets (billions) vs Consumer Sentiment 1.6 Fits Regress Lowess Tickets (billions) 1.5 1.4 1.3 1.2 60 70 80 90 Consumer Sentiment 100 110 R sq=5.1% Non-Parametric Correlation - Kendall • Null: x and y are independent vs Alternative: x and y are dependent in some way • Test stat: Tau – Tau > 0 = positively correlated – Tau < 0 = negatively correlated – Tau = 0 = no correlation Kendall’s Tau: Ticket Sales vs… Recession Prob : z = 0.414 p-value = 0.6789 Tau = 0.075 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and the probability of a recession. Kendall’s Tau: Ticket Sales vs… Real GDP per capita: z = 0 p-value = 1 Tau = 0 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and real GDP per capita. Kendall’s Tau: Ticket Sales vs… Unemployment rates: z = -0.4968 p-value = 0.6193 Tau = -0.09 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and unemployment rates. Kendall’s Tau: Ticket Sales vs… Stress Index: z = 0.6613 p-value = 0.5084 Tau = 0.119 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and stress levels. Kendall’s Tau: Ticket Sales vs… Consumer Sentiment: z = 0.992 p-value = 0.3212 Tau = 0.179 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and consumer sentiment. Kendall’s Tau: Ticket Sales vs… Velocity of money: z = 0.0827 p-value = 0.9341 Tau = 0.0149 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and velocity of money. Kendall’s Tau: Ticket Sales vs… S&P 500 Index: z = -0.248 p-value = 0.804 Tau = -0.0448 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and end value of S&P 500 Index. Kendall’s Tau: Ticket Sales vs… Public Debt: z = -0.5787 p-value = 0.5628 Tau = -0.1044 Fail to reject null and conclude there isn’t sufficient evidence that there is a correlation between ticket sales and public debt. Kruskal-Wallis Test Kruskal-Wallis • Null: Tau1 = Tau2 = Tau3 … = Tauk vs Alternative: Atleast one Tau differs Test stat = H Kruskal-Wallis Results • Because no correlation between any of the variables, it is no surprise that all KW tests resulted in a failure to reject the null hypothesis. Conclusion • Movie theatre attendance not influenced by economic factors Works Cited Economic Data http://research.stlouisfed.org/fred2/ Movie Theatre Data http://www.the-numbers.com/market/