Explain the results from the linear regression analysis. Pearson Correlation Test Table 1: REC * REV Correlation

Explain the results from the linear regression analysis. 

  

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Pearson Correlation Test Table 1: REC * REV Correlation REC REV REC Pearson Correlation 1 .677** Sig. (2-tailed) .000 N 618 618 REV Pearson Correlation .677** 1 Sig. (2-tailed) .000 N 618 618 ** Correlation is significant at the 0.01 level (2-tailed). Chi-Square (x) Test Table 2: Ticket * Attendance type Cross-tabulation Attendance With adults no kids type With Kids Alone Total Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases Ticket type Others Friends-purchased Seasonal Self-purchased Total 5 17 17 7 46 6 18 158 103 285 5 16 4 32 246 287 39 207 356 618 Table 3: Chi-Square Test Value 253.115a df Asymptotic Significance (2-sided) 6 .000 228.965 6 .000 156.359 1 .000 618 a. 2 cells (16.7%) have expected count less than 5. The minimum expected count is 1.19. Linear regression Table 4: Model Summary Std. Error Change Statistics R Adjusted R Square .111 Model R Square 1 .334a a. Predictors: (Constant). SAT. PGQ. ticket type, attendance type of the Estimate .105 1.283 R Square Change .111 F Change df1 df2 19.093 4 610 Sig. F Change .000 Pearson Correlation Test Table 1: REC * REV Correlation REC REV REC Pearson Correlation 1 .677** Sig. (2-tailed) .000 N 618 618 REV Pearson Correlation .677** 1 Sig. (2-tailed) .000 N 618 618 ** Correlation is significant at the 0.01 level (2-tailed). Chi-Square (x) Test Table 2: Ticket * Attendance type Cross-tabulation Attendance With adults no kids type With Kids Alone Total Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases Ticket type Others Friends-purchased Seasonal Self-purchased Total 5 17 17 7 46 6 18 158 103 285 5 16 4 32 246 287 39 207 356 618 Table 3: Chi-Square Test Value 253.115a df Asymptotic Significance (2-sided) 6 .000 228.965 6 .000 156.359 1 .000 618 a. 2 cells (16.7%) have expected count less than 5. The minimum expected count is 1.19. Linear regression Table 4: Model Summary Std. Error Change Statistics R Adjusted R Square .111 Model R Square 1 .334a a. Predictors: (Constant). SAT. PGQ. ticket type, attendance type of the Estimate .105 1.283 R Square Change .111 F Change df1 df2 19.093 4 610 Sig. F Change .000