HLT362V Applied Statistic For Health Care Professionals

pages Pages: 4word Words: 890

Question :

HLT362V Applied Statistic For Health Care Professionals

 Grand Canyon University USA

Question:

How would you characterize the skewness of the distribution in Question 1—positively skewed, negatively skewed, or approximately normal? Provide a rationale for your answer. The distribution in question 1 is skewed positively, when a skewed is positive it has the most statistic and it’s also more to the right side and the data is mostly on the right side, most people that participate in this study were mainly older generation. If it was a negative skewed it would be pointed more to the left meaning younger people participated.

Compare the original skewness statistic and Shapiro-Wilk statistic with those of the smaller dataset (n = 15) for the variable “Age at First Arrest.” How did the statistics change, and how would you explain these differences? When the original skewness statistic and Shapiro-Wilk is being compared, the original study n=20 and the n=15 has less skewness statistic. The graph of the n=15 shows a natural distribution than the original one. The new data value also is lower, the Shapiro-Wilk new statistic shows a p value of 0.211 and the new data statistic is within normal range where p is greater than 0.05.

Show More

Answer :


Age at Enrollment
 
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
41
1
6.7
6.7
6.7
43
1
6.7
6.7
13.3
47
1
6.7
6.7
20.0
49
1
6.7
6.7
26.7
52
2
13.3
13.3
40.0
56
3
20.0
20.0
60.0
58
1
6.7
6.7
66.7
60
2
13.3
13.3
80.0
62
1
6.7
6.7
86.7
63
2
13.3
13.3
100.0
Total
15
100.0
100.0
 

The distribution in question 1 is skewed positively, when a skewed is positive it has the most statistic and it’s also more to the right side and the data is mostly on the right side, most people that participate in this study were mainly older generation. If it was a negative skewed it would be pointed more to the left meaning younger people participated. 

Age at 1st Arrest
 
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
12
1
6.7
6.7
6.7
14
1
6.7
6.7
13.3
16
1
6.7
6.7
20.0
17
1
6.7
6.7
26.7
19
1
6.7
6.7
33.3
20
1
6.7
6.7
40.0
23
1
6.7
6.7
46.7
27
1
6.7
6.7
53.3
28
1
6.7
6.7
60.0
29
1
6.7
6.7
66.7
31
1
6.7
6.7
73.3
38
1
6.7
6.7
80.0
42
1
6.7
6.7
86.7
43
1
6.7
6.7
93.3
59
1
6.7
6.7
100.0
Total
15
100.0
100.0
 

 

Descriptives
 
Statistic
Std. Error
Age at Enrollment
Mean
54.53
1.818
95% Confidence Interval for Mean
Lower Bound
50.64
 
Upper Bound
58.43
 
5% Trimmed Mean
54.81
 
Median
56.00
 
Variance
49.552
 
Std. Deviation
7.039
 
Minimum
41
 
Maximum
63
 
Range
22
 
Interquartile Range
11
 
Skewness
-.622
.580
Kurtosis
-.600
1.121
Age at 1st Arrest
Mean
27.87
3.366
95% Confidence Interval for Mean
Lower Bound
20.65
 
Upper Bound
35.09
 
5% Trimmed Mean
27.02
 
Median
27.00
 
Variance
169.981
 
Std. Deviation
13.038
 
Minimum
12
 
Maximum
59
 
Range
47
 
Interquartile Range
21
 
Skewness
.990
.580
Kurtosis
.746
1.121

 

Tests of Normality
 
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
Age at Enrollment
.183
15
.192
.927
15
.248
Age at 1st Arrest
.138
15
.200*
.923
15
.211
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction

When the original skewness statistic and Shapiro-Wilk is being compared, the original study n=20 and the n=15 has less skewness statistic. The graph of the n=15 shows a natural distribution than the original one. The new data value also is lower, the Shapiro-Wilk new statistic shows a p value of 0.211 and the new data statistic is within normal range where p-value is greater than 0.05.

Q4. The way I would describe the Kurtosis of the question 4 distribution is leptokurtic, which is where the distribution is bunched around the mean which results higher

Statistics
Age at Enrollment
N
Valid
15
Missing
0
Skewness
-.622
Std. Error of Skewness
.580

The Skewness statistic can be reviewed in the data below it is 0.622. a skewness that is negative means most of statistic tail is on the left, which can be seen in the data below. The table shows that the data is a little bit skewed because the value between -1 and -1/2 or 1 and ½ is moderate.

Statistics
Years of Education
N
Valid
15
Missing
0
Skewness
.658
Std. Error of Skewness
.580
Kurtosis
-.936
Std. Error of Kurtosis
1.121

The kurtosis for years of education is 0.936, when a value is negative for a kurtosis it means the tail of the statistic is light, and the data is mainly around the mean. Meaning the magnitude is less than one, meaning the value of kurtosis is moderate.

Tests of Normality
 
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
Number of Times Fired from Job
.311
15
.000
.737
15
.001
a. Lilliefors Significance Correction

Using the SPSS with the Shapiro-Wilk it’s a test that diverge from a normal distribution, meaning if a p value is less than 0.05 it can be used to verify if a distribution is normal or not. In this example the value 0.001 meaning the number is not standard from the amount of times getting tired from a job.

The Kolmogorov-Smirnov is inappropriate to report because its usually used for larger sample sizes, normally it’s not being used until the samples sizes got to 2,000.

 It’s not very uncommon for the skewness to be low and the Shapiro-Wilk to be high. Skewness measures the moves over of the tail of the graph from the mean, if its low the tails becomes equal and they move over from the mean. On the other hand the Shapiro-Wilk look at the whole shape of the distribution all together, meaning the data may be non-parametric, or doesn’t follow any distribution at all.