A screening program for neuroblastoma (a type of cancer) was undertaken in Germany among children born between November 1, 1993, and June 30, 2000, who were between 9 and 18 months of age between May 1995 and April 2000. A total of 1,475,773 children participated in the screening program. Of whom 204 were diagnosed between 12 and 60 months of age. The researchers expected the incidence rate of neuroblastoma to be 7.3 per 100,000 children during this period in the absence of screening. We wish to test if the number of cases detected by the screening program is significantly greater than expected.

a) Write hypotheses to test this claim. Explain why you should use a one sided alternative.

b) You may assume any necessary conditions have been met. Perform your test.

c) Do you think that the number of cases detected by the screening program is significantly greater than expected? Explain.

d) Give a 95% confidence interval for the incidence rate of neuroblastoma in the screened population.

e) Express your confidence interval from part d) as (p1, p2), where p1 and p2 are in the units of number of cases per 100,000 children.

specifically need help with question e

How would you ensure that your sample is not biased?

What are the effects of a large sample size to the distribution of the bell curve?

Is smoking during pregnancy associated with premature births? To investigate this question, researchers selected a random sample of 148 pregnant women who were smokers. The average pregnancy length for this sample of smokers was 262 days. From a large body of research, it is known that length of human pregnancy has a standard deviation of 16 days. The researchers assume that smoking does not affect the variability in pregnancy length.

Find the 95% confidence interval to estimate the length of pregnancy for women who smoke.

(Note: The critical z-value to use, zc, is: 1.960)

( , )

Your answer should be rounded to 3 decimal places.

Imagine that you are a physician and you have just received the results back for a patient of yours who has just tested positive for the “heartbreak of psoriasis”. The test used will correctly label a person who is suffering from the “heartbreak of psoriasis” as a sufferer 90% of the time and will correctly label a person who is not suffering from the “heartbreak of psoriasis” as not being a sufferer 60% of the time. If the base-rate of suffering from the “heartbreak of psoriasis” is 5%, explain to your patient how likely she is actually suffering from the “heartbreak of psoriasis” on the basis of this positive result.

I got 7.32% using Bayes Theorem. Is this right?

What are​ companies' biggest obstacles to attracting the best​ talent? Of 1,000 surveyed U.S. and Canadian talent acquisition​ professionals, 510 reported that competition for talent is the biggest obstacle at their company. At the 0.01 level of​ significance, is there evidence that the proportion of all talent acquisition professionals who report competition is the biggest obstacle to attracting the best talent at their company is different from 47​%?

1. Calculate the test statistic ZSTAT.
2. Identify the​ p-value from your technology​ output, rounding to three decimal places.
3. Conclusion: Is there significant evidence to conclude that there is strong evidence in support of the claim that the proportion of all talent acquisition professionals who report competition is the biggest obstacle to attracting the best talent at their company is different from 61​%. ​

As part of a study of wheat maturation, an agronomist selected a sample of wheat plants at random from a field plot. For each plant, the agronomist measured the moisture content from two locations: one from the central portion and one from the top portion of the wheat head. The agronomist hypothesizes that the central portion of the wheat head has more moisture than the top portion. What can the agronomist conclude with α = 0.01? The moisture content data are below.

a) What is the appropriate test statistic?
---Select--- na z-test One-Sample t-test Independent-Samples t-test Related-Samples t-test

b)
Condition 1:
---Select--- wheat maturation top portion moisture content wheat head central portion
Condition 2:
---Select--- wheat maturation top portion moisture content wheat head central portion

c) Compute the appropriate test statistic(s) to make a decision about H₀.
(Hint: Make sure to write down the null and alternative hypotheses to help solve the problem.)
critical value =  ; test statistic =
Decision:  ---Select--- Reject H0 Fail to reject H0

d) If appropriate, compute the CI. If not appropriate, input "na" for both spaces below.
[  ,  ]

e) Compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and/or select "na" below.
d =  ;   ---Select--- na trivial effect small effect medium effect large effect
r² =  ;   ---Select--- na trivial effect small effect medium effect large effect

f) Make an interpretation based on the results.

The central portion of the wheat head had significantly more moisture than the top portion.The central portion of the wheat head had significantly less moisture than the top portion.    There was no significant moisture difference between the central and top portion of the wheat head.

A manager of a large office responsible for sustainability conducted a survey amongst her staff to find out how they travelled to work, and how punctual they were. The survey results were, for those surveyed: 25% of the staff took a bus to work, 40% took a car to work and the remainder cycled or walked (the sustainable option). If a staff member took a bus they were late 20% of the time, if a staff member took a car they were late 15% of the time and the remainder (those who cycled or walked) were never late.

(a) Complete the tree diagram below by writing the relevant probabilities on each branch and at the ends of the branches.

(b) Use the tree diagram to answer the following. Write down the calculations needed to find the answers:

(i) What is the probability that a randomly chosen staff member was late to work?

(ii) Given that a staff member was late, what is the probability they came to work by bus?

Estimating Mean SAT Math Score

The SAT is the most widely used college admission exam. (Most community colleges do not require students to take this exam.) The mean SAT math score varies by state and by year, so the value of µ depends on the state and the year. But let’s assume that the shape and spread of the distribution of individual SAT math scores in each state is the same each year. More specifically, assume that individual SAT math scores consistently have a normal distribution with a standard deviation of 100. An educational researcher wants to estimate the mean SAT math score (μ) for his state this year. The researcher chooses a random sample of 616 exams in his state. The sample mean for the test is 481.

Find the 99% confidence interval to estimate the mean SAT math score in this state for this year.

(Note: The critical z-value to use, zc, is: 2.576.)

( , )

Your answer should be rounded to 3 decimal places.

1.A researcher is investigating the effect of a new drug to lower anxiety. The drug was shown to be safe in humans, and the researcher wants to test what dosage of the drug is needed. He assigned twenty participants with clinical anxiety disorder to four treatment groups, then gave each the treatment regimen for four weeks. At the end of the trial, the participants took an anxiety test. The scores, corrected for initial anxiety score, are reported in the table below. Lower scores indicate lower anxiety levels. Analyze the data to determine if there is any difference in anxiety scores between the groups, and if there is a difference, determine and explain which treatment is most effective

1. What kind of statistical test will you be performing?
2. Will you need to test for equal variance? If so, what are your results and how does that influence the next steps in your analysis?
3. What are your null and alternative hypotheses?
4. Discuss the results of your analysis. Will you accept or reject your null hypothesis? Why? What can you specifically say about the data?

Alcohol withdrawal occurs when a person who uses alcohol excessively suddenly stops the alcohol use. Studies have shown that the onset of withdrawal is experienced a mean of 40.5 hours after the last drink, with a standard deviation of 19 hours. A sample of 38 people who use alcohol excessively is to be taken. What is the probability that the sample mean time between the last drink and the onset of withdrawal will be 39 hours or more?

Carry your intermediate computations to at least four decimal places. Round your answer to at least three decimal places.

the amount of things that are done to understand a physical educational study was based on the data below. Homework number #1

1. The claimed height (which is in inches) and weights (which is in pounds) of animals is significantly correlated, mean row(p) 0. Data has been collected which is below. Test this claim with statkey at a 5% significance level (alpha) and find the 98% confidence interval (using percentiles) for the true correlation between height and weight. Explain the test results consistent with the confidence interval and why? Note there are two statkey involved.

2. What is the Ho and Ha?

3. What is your alpha?

4. What is your p-value?

5. Conclusion?

6. 98% confidence interval?

7. Is it consistent?

8. Can you conclude multiple testing to be a good or bad idea in general and why?

A medical researcher wants to begin a clinical trial that involves systolic blood pressure (SBP) and cadmium (Cd) levels. However, before starting the study, the researcher wants to confirm that higher SBP is associated with higher Cd levels. Below are the SBP and Cd measurements for a sample a participants. What can the researcher conclude with an α of 0.01?

a) What is the appropriate statistic?
---Select--- na Correlation Slope Chi-Square
Compute the statistic selected above:

b) Compute the appropriate test statistic(s) to make a decision about H₀.
(Hint: Make sure to write down the null and alternative hypotheses to help solve the problem.)
critical value =  ; test statistic =
Decision:  ---Select--- Reject H0 Fail to reject H0

c) Compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and/or select "na" below.
effect size =  ;   ---Select--- na trivial effect small effect medium effect large effect

d) Make an interpretation based on the results.

There was a significant positive relationship between systolic blood pressure and cadmium levels.There was a significant negative relationship between systolic blood pressure and cadmium levels.    There was no significant relationship between systolic blood pressure and cadmium levels.

Two groups of students are selected to test different learning techniques. The test scores of group 1 were: 95, 73, 68, 95, 98, 79, 98, 86, 76, 89, 89, 94. The test scores of group 2 were: 100, 80, 95, 90, 95, 98, 100, 100. Can it be said with 95% confidence that one group outperformed the other?

Q.1: The iris dataset (included with R) contains four measurements for 150 flowers representing three species of iris (Iris setosa, versicolor and virginica). 1. Inspect the Iris data in R. 2. Use the summary code in R to perform descriptive analysis. Paste Summary statistics in your report. 3. Draw a scatter plot, for petal length vs petal width. 4. Find all possible correlation between quantitative variables. 5. Use Function lm for developing a regression model and paste the summary of the regression model in your report----Petal.Width ~ Petal.Lengt and for Sepal.Length ~ Sepal.Width