Brendan Couvreux

Instructor Larry Green

Math 201

18 March 2003

 

The Project

            I surveyed 51 professional ski patrollers at Heavenly mountain resort and asked, on average, how many days they worked during the winter season and how many days they worked during the summer. Convenience sampling was used for this survey. Considering the fact that the 51 patrollers surveyed comprise almost the entire population of the professional ski patrol members at Heavenly ski resort, the results of this test can be used to represent the majority of professional ski patrollers in the Lake Tahoe Basin. The pie chart represents the proportion of days worked during the winter and days worked during the summer.

            It is observed that the average number of days worked during the winter is 112 days with a standard deviation of approximately 24 days. With a 95% confidence, we can say that the average number of days that a patroller works during the winter is between 105 days and 119 days. The median number of days worked during the winter for patrollers is 110 days. The 5% trimmed mean (meaning 5% of the data was eliminated at both ends in an effort to minimize outliers) for the number of days worked during the winter is 112 days. The minimum number of days worked during the winter is 60 days and the maximum is 170 days. There is a total range (from the minimum to the maximum number of days worked during the winter) of 110 days. The interquartile range (the difference between the 75th percentile and the 25th percentile) is 35 days for winter. The Box plot illustrates the maximum and minimum with the two “whiskers.” The bottom of the box represents the 25th percentile and the top of the box represents the 75th percentile. The line in the middle represents the median. The bar chart for winter illustrates the quantity of patrollers that worked 0-60 days, 61-70 days, 71-80 days, 81-90 days, 91-100 days, 101-110 days, 111-120 days, 121-130 days, 131-140 days, 141-150 days, 151-160 days, and 161-170 days.

The average number of days worked during the summer is 90 days with a standard deviation of approximately 34 days. With a 95% confidence, we can say that the average number of days that a patroller works during the summer is between 80 days and 100 days. The median number of days worked during the summer for patrollers is 85 days. The 5% trimmed mean (meaning 5% of the data was eliminated at both ends in an effort to minimize outliers) for the number of days worked during the summer is 87 days. The minimum number of days worked during the summer is 40 days and the maximum is 200 days. There is a total range (from the minimum to the maximum number of days worked during the summer) of 160 days. The interquartile range (the difference between the 75th percentile and the 25th percentile) is 30 days for summer. The bar chart for summer illustrates the quantity of patrollers that worked 0-40 days, 41-60 days, 61-80 days, 81-100 days, 101-120 days, 121-140 days, 141-160 days, 161-180 days, and 181-200 days.

With this data I have tested the hypothesis that patrollers work more days during the winter than they do during the summer: H0: m=0     H1:m>0  a=0.05 The resulting p value is 0.026. P is inferior to a, thus we reject H0 and accept H1. This means that with a 5% level of significance, Heavenly professional ski patrol members work more days during the winter than they do during the summer. The average difference between the number of days worked during the winter and summer is approximately 22 days with a standard deviation of 47 days. With a 95% confidence, we can say that Heavenly professional ski patrollers work between 9 and 35 days more during the winter than they do during the summer.

I have also tested the hypothesis that the more days patrollers work during the winter, the less days they will work during the summer: H0: R=0  H1: R<0  It is observed that the value of R is –0.311 and R2=0.097 with a standard error of estimate SE=22.86. This means that 9.7% of the variations of the number of summer days worked is explained and 90.3% of the variations of the number of summer days worked is unexplained. We observe here a low correlation showing little relation between the number of days worked during the winter and number of days worked during the summer. The scatter diagram represents the number of days that each patroller works during summer and winter. The x axis being the number of days worked during the winter and the y axis being the number of days worked during the summer. The equation of the regression line is: y=131.651-0.217x. –0.217 is the slope of the regression line and 131.651 is the y intercept.



Paired Samples Statistics

 

Mean

N

Std. Deviation

Std. Error Mean

Pair 1

WINTER

112.0980

51

23.81198

3.33434

SUMMER

89.9608

51

34.07167

4.77099

 

Paired Samples Correlations

 

N

Correlation

Sig.

Pair 1

WINTER & SUMMER

51

-.311

.026

Paired Samples Test

 

Paired Differences

t

df

Sig. (2-tailed)

Mean

Std. Deviation

Std. Error Mean

95% Confidence Interval of the Difference

Lower

Upper

Pair 1

WINTER - SUMMER

22.1373

47.24956

6.61626

8.8481

35.4264

3.346

50

.002

Variables Entered/Removed(b)

 

Model

Variables Entered

Variables Removed

Method

1

SUMMER(a)

.

Enter

a All requested variables entered.

b Dependent Variable: WINTER

Model Summary

 

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.311(a)

.097

.078

22.86093

a Predictors: (Constant), SUMMER

ANOVA(b)

 

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

2742.036

1

2742.036

5.247

.026(a)

Residual

25608.474

49

522.622

Total

28350.510

50

a Predictors: (Constant), SUMMER

b Dependent Variable: WINTER

Coefficients(a)

 

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

131.651

9.117

14.441

.000

SUMMER

-.217

.095

-.311

-2.291

.026

a Dependent Variable: WINTER

One-Sample Statistics

 

N

Mean

Std. Deviation

Std. Error Mean

WINTER

51

112.0980

23.81198

3.33434

SUMMER

51

89.9608

34.07167

4.77099

One-Sample Test

 

Test Value = 0

t

df

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

Lower

Upper

WINTER

33.619

50

.000

112.0980

105.4008

118.7953

SUMMER

18.856

50

.000

89.9608

80.3780

99.5436

Case Processing Summary

 

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

WINTER

51

100.0%

0

.0%

51

100.0%

SUMMER

51

100.0%

0

.0%

51

100.0%

Descriptives

 

Statistic

Std. Error

WINTER

Mean

112.0980

3.33434

95% Confidence Interval for Mean

Lower Bound

105.4008

Upper Bound

118.7953

5% Trimmed Mean

111.8954

Median

110.0000

Variance

567.010

Std. Deviation

23.81198

Minimum

60.00

Maximum

170.00

Range

110.00

Interquartile Range

35.0000

Skewness

.187

.333

Kurtosis

-.197

.656

SUMMER

Mean

89.9608

4.77099

95% Confidence Interval for Mean

Lower Bound

80.3780

Upper Bound

99.5436

5% Trimmed Mean

86.7429

Median

85.0000

Variance

1160.878

Std. Deviation

34.07167

Minimum

40.00

Maximum

200.00

Range

160.00

Interquartile Range

30.0000

Skewness

1.615

.333

Kurtosis

3.497

.656

WINTER Stem-and-Leaf Plot

Frequency Stem & Leaf

.00 0 .

3.00 0 . 677

11.00 0 . 88889999999

15.00 1 . 000000000011111

14.00 1 . 22222222233333

6.00 1 . 444455

2.00 1 . 67

Stem width: 100.00

Each leaf: 1 case(s)

 

 

SUMMER Stem-and-Leaf Plot

Frequency Stem & Leaf

2.00 4 . 00

3.00 5 . 000

7.00 6 . 0000555

7.00 7 . 0005558

7.00 8 . 0000005

7.00 9 . 0000005

8.00 10 . 00000000

4.00 11 . 0000

2.00 12 . 00

4.00 Extremes (>=150)

Stem width: 10.00

Each leaf: 1 case(s)