plz run in r studio n answer all the questions biostats........ Worksheet T tests, Wilcoxon’s test, Mc Nemar’s Test Answer the following questions using R studio and submit the MS word format from via Moodle. 1. Test whether the marginal probabilities are the same or different for the following dataset. Create the dataset by using the following Scripts: > set.seed(50) >data <- data.frame(before = sample(c("Positive",  "Positive",  "Positive",  "Positive",  "Negative"),  250, replace = TRUE),  after = sample(c("Positive",  "Positive",  "Positive",  "Positive",  "Negative"),  250, replace = TRUE)) >data Note: Prepare a contingency table using the table function, before choosing and running your analysis. 2. The following data were recorded as independent observations for heights (cm) of Guava Plants treated with NPK nutrients. We want to know, if the average height of the these plants statistically differs from 19 cm? 18.50, 18.55, 18.60, 18.65, 18.70, 18.75, 18.80, 18.85, 18.90, 18.95, 19.00, 19.05,19.10, 19.15, 19.20, 19.25, 19.30, 19.35, 19.40, 19.45, 19.50, 19.55, 19.60, 19.65,19.70, 19.75, 19.80, 19.85, 19.90, 19.95, 20.00, 20.05, 20.10, 20.15, 20.20, 20.25, 20.30, 20.35, 20.40, 20.45, 20.50 Choose the appropriate statistical test (s) to answer your questions and determine if the hypothesis is left or right tailed. 3. Sample scores from a BIO3211 test yield these results from tutorial sessions. 8,7,10,8,9,10,8,10,7,10,8,10,6,8,10,9,10,7,10,10,7,10,8,10,6,8,10,9, 10,7 Test whether there is a significant difference from the theoretical value of a score of 7. Would the hypothesis be left or right tailed?

plz run in r studio n answer all the questions

biostats........ Worksheet T tests, Wilcoxon’s test, Mc Nemar’s Test
Answer the following questions using R studio and submit the MS
word format from via Moodle.
1. Test whether the marginal probabilities are the same or different
for the following dataset. Create the dataset by using the following
Scripts:
> set.seed(50)
>data <- data.frame(before = sample(c("Positive",
 "Positive",
 "Positive",
 "Positive",
 "Negative"),
 250, replace = TRUE),
 after = sample(c("Positive",
 "Positive",
 "Positive",
 "Positive",
 "Negative"),
 250, replace = TRUE))
>data
Note: Prepare a contingency table using the table function, before
choosing and running your analysis.
2. The following data were recorded as independent observations
for heights (cm) of Guava Plants treated with NPK nutrients. We
want to know, if the average height of the these plants statistically
differs from 19 cm?
18.50, 18.55, 18.60, 18.65, 18.70, 18.75, 18.80, 18.85, 18.90,
18.95, 19.00, 19.05,19.10, 19.15, 19.20, 19.25, 19.30, 19.35, 19.40,
19.45, 19.50, 19.55, 19.60, 19.65,19.70, 19.75, 19.80, 19.85, 19.90,
19.95, 20.00, 20.05, 20.10, 20.15, 20.20, 20.25, 20.30, 20.35,
20.40, 20.45, 20.50
Choose the appropriate statistical test (s) to answer your questions
and determine if the hypothesis is left or right tailed.
3. Sample scores from a BIO3211 test yield these results from
tutorial sessions.
8,7,10,8,9,10,8,10,7,10,8,10,6,8,10,9,10,7,10,10,7,10,8,10,6,8,10,9,
10,7
Test whether there is a significant difference from the theoretical
value of a score of 7. Would the hypothesis be left or right tailed?
4. Test the Null hypothesis that the Dart scores from Group A is not
different from Group B and or Group A scores are greater than or
less than Group B.
Group A: 1,2,2,3,3,4,4,5,5,6
Group B: 1,2,4,5,5,5,6,6,7,9
5. The pre and post tests scores for a randomly selected group of
students before and after exposure to new teaching methods are
as follows:
Pretest: 10,5,8,6,4,5,5,8,7,6,10,5, 8,6,4,5,5,8,7,6
Posttest: 10,6,8,8,5,4,5,9,10,7, 8,5,4,5,9,10,7,10,6,8
Is there a significant difference in performance before compared to
after exposure to a different teaching method?
6. Results for blood glucose levels independently taken for the
same individuals before and after treatment with sucrose solution
to determine impacts of carbohydrates on blood sugar levels are
outlined below:
before : 200.1, 190.9, 192.7, 213, 241.4, 196.9, 172.2, 185.5, 205.2,
193.7
after : 392.9, 393.2, 345.1, 393, 434, 427.9, 422, 383.9, 392.3,
352.2
Select the appropriate test statistic to test the Null Hypothesis for
the that H0=H1.
7. Test the null hypothesis that Group 1 scores not Equal to Group
2 scores using the appropriate test statistics .
Group1= 19, 18, 9, 17, 8, 7, 16, 19, 20, 9, 11, 18
Group2= 16, 5, 15, 2, 14, 15, 4, 7, 15, 6, 7, 14
8. Choose and perform the appropriate statistical test for the
following two samples to determine if their populations means
differ significantly at a significance level of 0.05:
Population Sample 1: 14, 15, 15, 15, 16, 18, 22, 23, 24, 25, 25
Population Sample 2: 10, 12, 14, 15, 18, 22, 24, 27, 31, 33, 34, 34,
34
Before conducting any test statistics, check to see assumptions (Write up
each of the following)
1. Identify your variable parameters
2. State you Null and Alternate Hypotheses
3. Check your data using descriptive statistics. What does the summary
say about
your data? Plot a box plot to visualise of the data
4. Check the assumptions
5. Is this a large sample n>30?
6. Check whether the data follow a normal distribution by:
7. Plot a Histogram or Q-Q plot to visualise the data to check for normal
distribution
8. Conduct a formal normality test and state the Null and alternate
Hypotheses
9. Is the Test a two tailed, or one tailed (left tailed or right tailed)
10. Choose and run the appropriate test Statistics on the data
11. Interpret results and Accept/Reject your Null Hypothesis.
12. Write your conclusion as discussed in the lectures and include your
Hypothesis, p
valve (alpha value), test statistics and degrees of freedom (df).
13. Set all significance level at 0.05 or where appropriate for nonparametric tests
14. Do you understand how now how to choose the appropriate statistics
and why?
Explain in your own words for each of the statistical test you ran.