Can you help me understand this regression output? Can you help me interpret the results and give managerial advice? What would you suggest to the client based on this output? SUMMARY OUTPUT Regression Statistics Multiple R: 0.99682244 R Square: 0.99365498 Adjusted R Square: 0.99214427 Standard Error: 17022.9253 Observations: 27 ANOVA df: 5 21 26 Ss: M5 Significance F: 9.52995E+11 1.906E+11 657.736917 2.52891E-22 6085379699 289779986 9.5908E+11 Regression Residual Total Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept: -2249.759 30390.834 -0.074 0.942 -65450.958 60951.439 -65450.958 60951.439 sq. ft.: 18.154 3.213 5.650 0.000 11.472 24.836 11.472 24.836 ad spending: 16.241 1.736 9.353 0.000 12.630 19.852 12.630 19.852 # of local households: 14.696 1.599 9.192 0.000 11.371 18.021 11.371 18.021 #=competitors in the area: -5064.445 1622.990 -3.120 0.005 8439.638 -1689.253 -8439.638 -1689.253 Opened last year (1 = yes; 0 = no): -34276.784 10128.541 -3.384 0.003 -55340.239 13213.329 55340.239 -13213.329 Annual Sales = -2249.7 + 18.15 * SQ,FT + 16.241 * ad spendings + 14.69 * number of local households - 5064.4 * number of competitors in the area - 34276.7 * freq, opened last year PROBABILITY OUTPUT Percentile Annual net sales 1.851851852 500 5.555555556 10000 9.259259259 15000 12.96296296 20000 16.66666667 65000 20.37037037 68000 24.07407407 98000 99000 31.48148148 156000 35.18518519 161000 38.88888889 195000 42.59259259 231000 46.2962963 299000 50 341000 53.7037037 347000 57.40740741 397000 61.11111111 398000 64.81481481 400000 68.51851852 428000 72.22222222 437000 75.92592593 464000 79.62962963 487000 497000 87.03703704 507000 90.74074074 519000 94.44444444 528000 98.14814815 570000
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Regression Statistics: - R: The multiple correlation coefficient, which measures the strength and direction of the linear relationship between the independent variables and the dependent variable. In this case, R = 0.9968, indicating a very strong positive Show more…
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SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.839168643 0.704204011 0.695504129 0.62867577 36 ANOVA df 31.9917926231.9918 80.9440875 13.43792960.39523 45.42972222 Significance F Regression Residual Total 3| 35 1.62589E-10 Coefficients Standard Error t Stat P-value 0.291093339 18.0032 5.8906E-19 0.009907724 -8.9969 1.6259E-10 Lower 95% Upper 95% Intercept 4.649041127 5.83219 Program Participation Rate (%) -0.109273652 -0.069 RESIDUAL OUTPUT Observation Predicted Nurse Attrition Rate (%) 4.340312752 4.215518525 4.43836536 4.295743385 3.974843943 3.698513867 3.734169361 3.6539445 3.440011538 3.502408652 3.520236399 3.885705208 3.181509209 3.128025969 3.092370475 3.012145614 2.985403994 2.940834627 2.700160045 2.45057159 2.654504551 2.459485463 2.388174476 2.50405483 2.200983134 2.183155387 1.995964046 1.71963397 1.817686578 1.764203337 1.66615073 1.630495236 1.487873261 1.380906781 1.318509667 1.32742354 Residuals 0.340312752 0.215518525 1.06163464 -0.595743385 -0.274843943 0.001486133 -0.234169361 0.1460555 0.059988462 0.097591348 -0.220236399 2.114294792 0.118490791 1.928025969 0.007629525 0.012145514 -0.085403994 -0.440834627 -0.200160045 0.14942841 0.164504551 -0.359485463 -0.488174476 -0.30405483 0.100983134 0.916844613 0.204035954 0.08036503 0.682313422 1.035796663 -0.16615073 -0.130495236 -0.187873261 -0.180906781 -0.218509667 0.17257646
Sri K.
help me please
Keondre P.
Adi S.
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