University of Missouri Kansas City Statistics Worksheet

This is a statistical research on the fatality rates caused by commercial air travel vs fatality rates caused by the automobiles from 2000-2020. Try to use commercial air travel in the USA vs automobiles deaths in the USA. I am trying to prove statically that air travel is safer. (Will attach my classmates post for you to respond to and see it as an example response is 50 words) You will be using the T test function in stat crunch (will provide login credentials) Will also provide the null hypothesis.

You will need to research data for this post, or this discussion, present your hypothesis test and your conclusion based on the results.

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Start by presenting your research and null hypotheses. Discuss the data and statistical test type, and then you can copy/paste your results from StatCrunch. Finally, state if you reject/fail to reject the null hypothesis and what this means.

When providing feedback to others in this thread, let each other know whether or not you clearly understand the conclusions.

STUDENT 2
The topic which is going to be analyzed is whether covid 19 affected passengers
traveling on airlines in the United States. The year 2019 will be compared to the year
2020 and looked at thoroughly, and the number of passengers will be compared during
each month of the year for domestic air travel in the United States. The dependent
variable in the analysis will be the number of passengers travelling as this statistic was
directly impacted by the number of covid 19 cases occurring, hence it is chosen as the
dependent variable. The independent variable is the number of covid cases as covid 19
was independent of the other dataset being analyzed (number of passengers traveling).
The question which this statistical analysis aims to answer is whether covid 19 affected
the number of passengers traveling in airlines or not. To answer this question, there are
two hypotheses formed during the study:
Hypotheses:
Null Hypothesis Ho: The number of passengers traveling in 2019 is the same as the
number of passengers traveling in 2020 and there was no difference between them. H1
= H2
Alternate hypothesis Ha: The number of passengers traveling domestically on airlines in
the USA were not the same. There was a notable decrease in the number of passengers
traveling during covid 19 (2020) compared to before covid 19(2019). H2 < H1 Population A: Number of passengers traveling domestically in 2019 in the USA Population B: Number of passengers traveling domestically in 2020 in the USA The data of the 2 years is attached below: All rights are reserved. The material contained herein is the copyright property of Embry-Riddle Aeronautical University, Daytona Beach, Florida, 32114. No part of this material may be reproduced, stored in a retrieval system or transmitted in any form, electronic, mechanical, photocopying, recording or otherwise without the prior written consent of the University. College of Aeronautics | worldwide.erau.edu The above table and data will be further analyzed in depth in the research paper using the 5 step hypothesis testing method. The analysis method which is being used is the T test. The results of the T test computed on StatCrunch are attached below: Error! Filename not specified. The test performed in this analysis is a one-tailed test, with 11 degrees of freedom (as the number of months are 12), and test is done with a 0.05 significance. The cutoff score T critical will be = 1.7958848. The value of T stat 5.9197626 is significantly greater than the T critical value of 1.7958848. All rights are reserved. The material contained herein is the copyright property of Embry-Riddle Aeronautical University, Daytona Beach, Florida, 32114. No part of this material may be reproduced, stored in a retrieval system or transmitted in any form, electronic, mechanical, photocopying, recording or otherwise without the prior written consent of the University. College of Aeronautics | worldwide.erau.edu The data has a normal distribution in the QQ plot with a correlation value of 0.977 and 0.934 in the years 2019 and 2020 respectively. This means that the data in both years is very strongly correlated. Error! Filename not specified. Error! Filename not specified. The cumulative correlation of data from both the years still have a correlation value of 0.921 implying a strong correlation of data. Error! Filename not specified. Conclusion: Since the value of T stat 5.9197626 is significantly greater than the T critical value of 1.7958848, it implies that the null hypothesis is rejected. The alternate hypothesis is correct i.e., the number of passengers who travelled in 2020 is significantly lesser than the number of passengers who travelled in 2019. This is further substantiated by the value in the 1st table above, indicating that 444.6 million more passengers travelled via airlines in 2019 compared to 2020. The mean amount of passengers in 2019 is significantly greater with an average of 65 million passengers traveling every month compared to an average of 27.9 million passengers traveling every month in 2020. All rights are reserved. The material contained herein is the copyright property of Embry-Riddle Aeronautical University, Daytona Beach, Florida, 32114. No part of this material may be reproduced, stored in a retrieval system or transmitted in any form, electronic, mechanical, photocopying, recording or otherwise without the prior written consent of the University. College of Aeronautics | worldwide.erau.edu

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