MATH 1300 week 4 Assignment: Project for module 4
- Assignment: Project for module 4
Student Name
William Penn University
MATH1300
Professor Name
Submission Date
Base on the given data uploaded, will you conclude that the number of bathroom of houses is a significant factor for house price? If your answer is affirmative, then explain how the house price is influenced by the number of bathroom?
| ANOVA | |||||
| Sprice | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Between Groups | 1813048.719 | 2 | 906524.359 | 9.114 | <.001 |
| Within Groups | 4675094.281 | 47 | 99470.091 | ||
| Total | 6488143.000 | 49 | |||
Ho: m1=m2
Ha: at least one of the means is different
P=<0.01; α= 0.05 Since P is less than α, reject Ho
Conclusion: At least one mean is different. In this instance, at least one group (number of bathrooms) means different mean price.
Post Hoc Tests
Homogeneous Subsets
| Sell Price | |||
| Student-Newman-Keulsa,b | |||
| BTHRMS | N | Subset for alpha = 0.05 | |
| 1 | 2 | ||
| 1.00 | 17 | 641.7647 | |
| 2.00 | 24 | 872.0833 | |
| 3.00 | 9 | 1193.8889 | |
| Sig. | .058 | 1.000 | |
| Means for groups in homogeneous subsets are displayed. | |||
| a. Uses Harmonic Mean Sample Size = 14.178. | |||
| b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. | |||
m1= Mean of sell price with 1 bathroom;
m2= Mean of sell price with 2 bathrooms
m3= Mean of sell price with 3 bathrooms
m1=m2
m3> m1,m2
The mean sell price with 1 bathroom is similar to the mean sell price with 2 bathrooms
The mean sell price of 3 bathrooms is higher than the mean sell price of 1 bathroom and 2 bathroom houses.
Conclusion:
The prices of houses with 1 bathroom and 2 bathrooms are not statistically different. However, the price of houses with 3 bathrooms are significantly higher statistically than both houses with 1 bathroom and 2 bathrooms.
Non parametric test for sell price with 1 bathroom
| One-Sample Kolmogorov-Smirnov Test | |||
| VAR00011 | |||
| N | 17 | ||
| Normal Parametersa,b | Mean | 641.7647 | |
| Std. Deviation | 113.78696 | ||
| Most Extreme Differences | Absolute | .182 | |
| Positive | .101 | ||
| Negative | -.182 | ||
| Test Statistic | .182 | ||
| Asymp. Sig. (2-tailed)c | .137 | ||
| Monte Carlo Sig. (2-tailed)d | Sig. | .130 | |
| 99% Confidence Interval | Lower Bound | .122 | |
| Upper Bound | .139 | ||
| a. Test distribution is Normal. | |||
| b. Calculated from data. | |||
| c. Lilliefors Significance Correction. | |||
| d. Lilliefors’ method based on 10000 Monte Carlo samples with starting seed 2000000. | |||
Non parametric test for sell price with 2 bathroom
| One-Sample Kolmogorov-Smirnov Test | |||
| VAR00012 | |||
| N | 24 | ||
| Normal Parametersa,b | Mean | 872.0833 | |
| Std. Deviation | 184.21937 | ||
| Most Extreme Differences | Absolute | .179 | |
| Positive | .179 | ||
| Negative | -.114 | ||
| Test Statistic | .179 | ||
| Asymp. Sig. (2-tailed)c | .046 | ||
| Monte Carlo Sig. (2-tailed)d | Sig. | .045 | |
| 99% Confidence Interval | Lower Bound | .040 | |
| Upper Bound | .051 | ||
| a. Test distribution is Normal. | |||
| b. Calculated from data. | |||
| c. Lilliefors Significance Correction. | |||
| d. Lilliefors’ method based on 10000 Monte Carlo samples with starting seed 299883525. | |||
Non parametric test for sell price with 3 bathroom
| One-Sample Kolmogorov-Smirnov Test | |||
| VAR00013 | |||
| N | 9 | ||
| Normal Parametersa,b | Mean | 1193.8889 | |
| Std. Deviation | 678.91355 | ||
| Most Extreme Differences | Absolute | .234 | |
| Positive | .234 | ||
| Negative | -.222 | ||
| Test Statistic | .234 | ||
| Asymp. Sig. (2-tailed)c | .169 | ||
| Monte Carlo Sig. (2-tailed)d | Sig. | .171 | |
| 99% Confidence Interval | Lower Bound | .161 | |
| Upper Bound | .180 | ||
| a. Test distribution is Normal. | |||
| b. Calculated from data. | |||
| c. Lilliefors Significance Correction. | |||
| d. Lilliefors’ method based on 10000 Monte Carlo samples with starting seed 926214481. | |||