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Submitted By Apusaha57
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Problem-2: Skewness | .592 | Statistics | Selling Price in $000 | N | Valid | 81 | | Missing | 0 | Std. Error of Skewness | .267 | a.

Interpretation: The coefficient of skewness is greater than zero (.529>0). So, the distribution of selling price is positively skewed. b. Case Processing Summary | | Cases | | Valid | Missing | Total | | N | Percent | N | Percent | N | Percent | Selling Price in $000 | 81 | 100.0% | 0 | .0% | 81 | 100.0% |

Interpretation: There is no outlier.
Problem-3:
a. One-Sample Test | | Test Value = 0 | | t | df | Sig. (2-tailed) | Mean Difference | 95% Confidence Interval of the Difference | | | | | | Lower | Upper | Distance from the center of the city | 25.624 | 80 | .000 | 14.593 | 13.46 | 15.73 |

Interpretation: The difference for the distance of the home from the center of the city is 14.59 and 95% confidence interval is 13.46 to 15.73

b. Garage attached | | | Frequency | Percent | Valid Percent | Cumulative Percent | Valid | No | 27 | 33.3 | 33.3 | 33.3 | | Yes | 54 | 66.7 | 66.7 | 100.0 | | Total | 81 | 100.0 | 100.0 | |

So proportion of home with garage, p= xn =5481 =0.67
Now 95% Confidence Interval for proportion of home with garage becomes, p±πp(1-p)n =0.67±1.960.67(1-.067)81
=0.67±0.011
= 0.659 to 0.681
Interpretation:95% confidence Interval for the homes with an attached garage is 0.659 to 0.681

Problem-4:
a.
Step-1:Null Hypothesis, Ho: µ ≤ 200 Alternative Hypothesis, H1 : µ >200
Step-2: Level of significance, α =0.01
Step-3: T- test statistics will be used
Step-4: P< α, we may reject Ho P> α, we may not reject Ho
Step-5:
One-Sample

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