\ufeffMat section 8<\/p>\n
Name<\/p>\n
Professor<\/p>\n
Institution<\/p>\n
Course<\/p>\n
Date<\/p>\n
Description<\/p>\n
The unemployment data is important to the United States in making macro and microeconomic policies (Rufus, 2010). The average of the unemployment is 7.767, which is the general average of unemployment in all the states. However, at 95% critical value, the standard deviation is 1.88 while the variance from the mean is 3.554. This shows that the variances between the figures of mean are large enough. Cowan, (2012), the disparity is large due to the economic activities and endowment of various regions. On the other hand, the Skewedness is less than 4 and the Kurtosis is less than then 2, this means that the data do not violate the assumptions of the statistical analyses. The Skewedness and kurtosis is within the acceptable limits (Gary, Elder, Fast &, Hill, 2012; Kimberly, 2007).<\/p>\n
Descriptive statistic<\/p>\n
Anderson-Darling A-Squared 0.100<\/p>\n
p 0.996<\/p>\n
95% Critical Value 0.787<\/p>\n
99% Critical Value 1.092<\/p>\n
Mean 7.767<\/p>\n
Mode 6.800<\/p>\n
Standard Deviation 1.885<\/p>\n
Variance 3.554<\/p>\n
Skewedness -0.016<\/p>\n
Kurtosis 0.102<\/p>\n
N 52.000<\/p>\n
Minimum 3.300<\/p>\n
1st Quartile 6.600<\/p>\n
Median 7.900<\/p>\n
3rd Quartile 9.000<\/p>\n
Maximum 12.600<\/p>\n
Confidence Interval 0.525<\/p>\n
for Mean (Mu) 7.242<\/p>\n
0.95 8.292<\/p>\n
For Stdev (sigma) 1.580<\/p>\n
2.338<\/p>\n
for Median 7.000<\/p>\n
8.300<\/p>\n
.<\/p>\n
Anova: Two Factor With Replication \u03b1 0.05 SUMMARY Data1 Total Nevada \u00a0 \u00a0 Count 2 2 Sum 23.7 23.7 Average 11.85 11.85 Variance 1.125 1.125 Rhode Island \u00a0 \u00a0 Count 2 2 Sum 21.2 21.2 Average 10.6 10.6 Variance 0.08 0.08 Mississippi \u00a0 \u00a0 Count 2 2 Sum 20.3 20.3 Average 10.15 10.15 Variance 0.125 0.125 North Carolina \u00a0 \u00a0 Count 2 2 Sum 19.7 19.7 Average 9.85 9.85 Variance 0.005 0.005 Georgia \u00a0 \u00a0 Count 2 2 Sum 19.2 19.2 Average 9.6 9.6 Variance 0.02 0.02 Michigan \u00a0 \u00a0 Count 2 2 Sum 18.4 18.4 Average 9.2 9.2 Variance 0.02 0.02 Indiana \u00a0 \u00a0 Count 2 2 Sum 18 18 Average 9 9 Variance 0 0 Oregon \u00a0 \u00a0 Count 2 2 Sum 17.6 17.6 Average 8.8 8.8 Variance 0.02 0.02 Arizona \u00a0 \u00a0 Count 2 2 Sum 17 17 Average 8.5 8.5 Variance 0.08 0.08 Washington \u00a0 \u00a0 Count 2 2 Sum 16.9 16.9 Average 8.45 8.45 Variance 0.005 0.005 Connecticut \u00a0 \u00a0 Count 2 2 Sum 16.3 16.3 Average 8.15 8.15 Variance 0.005 0.005 Ohio \u00a0 \u00a0 Count 2 2 Sum 16.1 16.1 Average 8.05 8.05 Variance 0.005 0.005 New York \u00a0 \u00a0 Count 2 2 Sum 15.9 15.9 Average 7.95 7.95 Variance 0.005 0.005 West Virginia \u00a0 \u00a0 Count 2 2 Sum 15.7 15.7 Average 7.85 7.85 Variance 0.005 0.005 Arkansas \u00a0 \u00a0 Count 2 2 Sum 15.3 15.3 Average 7.65 7.65 Variance 0.005 0.005 Delaware \u00a0 \u00a0 Count 2 2 Sum 14.7 14.7 Average 7.35 7.35 Variance 0.005 0.005 Wisconsin \u00a0 \u00a0 Count 2 2 Sum 14.1 14.1 Average 7.05 7.05 Variance 0.005 0.005 Louisiana \u00a0 \u00a0 Count 2 2 Sum 13.6 13.6 Average 6.8 6.8 Variance 0 0 Montana \u00a0 \u00a0 Count 2 2 Sum 13.5 13.5 Average 6.75 6.75 Variance 0.005 0.005 Hawaii \u00a0 \u00a0 Count 2 2 Sum 13.2 13.2 Average 6.6 6.6 Variance 0 0 Kansas \u00a0 \u00a0 Count 2 2 Sum 12.5 12.5 Average 6.25 6.25 Variance 0.005 0.005 Oklahoma \u00a0 \u00a0 Count 2 2 Sum 12.1 12.1 Average 6.05 6.05 Variance 0.005 0.005 Wyoming \u00a0 \u00a0 Count 2 2 Sum 11.5 11.5 Average 5.75 5.75 Variance 0.005 0.005 Iowa \u00a0 \u00a0 Count 2 2 Sum 10.7 10.7 Average 5.35 5.35 Variance 0.125 0.125 New Hampshire \u00a0 \u00a0 Count 2 2 Sum 9.3 9.3 Average 4.65 4.65 Variance 0.405 0.405 Nebraska \u00a0 \u00a0 Count 2 2 Sum 7.4 7.4 Average 3.7 3.7 Variance 0.32 0.32 Total \u00a0 \u00a0 Count 52 52 Sum 403.9 403.9 Average 7.767308 7.767308 Variance 3.554008 3.554008 k<\/p>\n
.<\/p>\n
X<\/p>\n
Exercise 1<\/p>\n
Ho: Saint Leo University is the largest of the three catholic Universities in Florida<\/p>\n
H1: Saint Leo University is not the largest of the three catholic universities in Florida<\/p>\n
23 20<\/p>\n
12 12<\/p>\n
23 45<\/p>\n
67 11<\/p>\n
46 13<\/p>\n
25 23<\/p>\n
45 21<\/p>\n
89 15<\/p>\n
t-Test: Two-Sample Assuming Unequal Variances \uf061 0.05<\/p>\n
Equal Sample Sizes \u00a0 Data1 Data2<\/p>\n
Mean 41.25 20<\/p>\n
Variance 680.7857 122<\/p>\n
Observations 8 8<\/p>\n
Hypothesized Mean Difference 0 df 9 t Stat 2.121 P(T<=t) one-tail 0.031 T Critical one-tail 1.833 P(T<=t) two-tail 0.063 T Critical Two-tail 2.262 \u00a0<\/p>\n
Decision<\/p>\n
Reject Null Hypothesis because p < 0.05 (Means are Different)<\/p>\n
Exercise 2:<\/p>\n
The sample data is as shown below: 62, 67, 71, 74, 76, 77,<\/p>\n
formula <\/p>\n
This is also expressed as <\/p>\n
Course assignment Assignment Grade Percentage of Course Grade<\/p>\n
A 62 10<\/p>\n
B 67 10<\/p>\n
C 71 30<\/p>\n
Total Percent Listed 50 Course Average for Listed Assignments 68.4 References<\/p>\n
Rufus K., (2010). “Unemployment rates – Unemployment rates by State”. CNN Money,<\/p>\n
Kimberly H., (2007). “What is the difference between seasonally adjusted and non-seasonally adjusted data?\u201d Nebraska Department of Labor. <\/p>\n
Cowan G., (2012).Statistical Data Analysis. Oxford Science Publications. Oxford.<\/p>\n
Gary M, J. Elder, A, Fast &T. Hill (2012), publisher Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications.NY Sage <\/p>\n","protected":false},"excerpt":{"rendered":"
\ufeffMat section 8 Name Professor Institution Course Date Description The unemployment data is important to the United States in making<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-52772","post","type-post","status-publish","format-standard","hentry"],"yoast_head":"\n