Relationships between home teams and visiting teams

A sports statistician is interested in determining if there is a relationship between the number of home team and visiting team losses and different sports. A random sample of 526 games is selected and the results are given below. Test the claim that the number of home and visiting losses is independent of the sport. Use alpha = 0.01
Football Basketball Soccer Baseball
Home team losses 39 156 25 83
Visiting team losses 31 98 19 75

Assessing Within Subject Effects

1. Using the SPSS output attached, interpret the data in the table for the within-subjects effects.
2. Make sure to discuss the findings of the analysis in terms of what they actually mean in the context of the study (example given in the lecture for the effects of room temperature on memory).

Statistics: Research Hypothesis

I need help with the following questions regarding the research hypothesis:
(All data has already been entered onto attachment.)

a) Identify and test the research hypothesis at the .05 level of significance that boys raise their hands in class more often than girls. Remember to first decide whether this is a one- or two-tailed test. What is your conclusion regarding the research hypothesis?

b) Test the research hypothesis at the .01 level of significance that there is a difference between boys and girls in the number of times they raise their hands in class. What is your conclusion regarding the research hypothesis?

c) You used the same data for both parts a and b, but you have a different hypothesis (one is directional and the other is non-directional). How do the results differ and why?

Scientific Methodology

What is the difference between qualitative and quantitative data? Provide an example of each type.

What is a null and alternative hypothesis?

What is a variable? What are independent and dependent variables?

What is the difference between population and sample? When would you want to use a sample? How would you go able obtaining a sample?

What is the difference between probability and non-probability sampling? Which sampling method would strengthen the research design? Why?

short description

Exercises 12-15 thru 12-17. Textbook PDF’s with questions omitted for copyright reasons. Refer to attachments for necessary data.

Please begin each solution by stating or restating the problem, establishing parameters, establishing the hypothesis, defining parameters used, and ending with both the statistical decision and business decision reached by the analysis.

Appropriate statistic tests

I have created the following hypothesis need help for approprate tests ( independant t test /correlation/regression/anova) and stating the hypothesis

1. What would you suggest to be the appropriate statistic tests to use and why ?

2. Any suggestions on stating the hypothesis in a more professional manner?
This is what I have so far

Null Hypothesis #1. There is no relationship between episodes of bullying and post-traumatic stress disorder.

Alternative Hypothesis #1. Post-traumatic stress disorder is directly related to episodes of bullying.

Null Hypothesis #2. There is no relationship with the severity of bullying episodes and post-traumatic stress disorder.

Alternative Hypothesis #2. The severity of bullying episodes is related to post-tramatic stress disorder.

Chi-Square with SPSS: gss04student Database, Race vs. Birth Defects

Can someone help me to condense the statistical results of the attached “Chi-square” done by the SPSS program? The test looks at: Is there a relationship between race and birth defects. I have included an example of how my I need to condensed the SPSS results paper in an APA format. I need help with answering the following questions in my paper.

-Craft up to a one page double-spaced write up of the statistical results in which you do the following:
-State the statistical assumptions for this test.
-Using the data set you have selected, choose independent and dependent variables.
-Develop the null hypothesis and the alternative hypothesis.
-Use SPSS to calculate a chi-square. (See Attached)
-Decide whether to reject or retain the null hypothesis.
-Generate syntax and output files in SPSS. (See Attached)

Graphs and rationale

A research team conducted a study of soft- drink preferences among residents in a test market prior to an advertising campaign for a new cola product. Of the participants, 130 are teenagers and 130 are adults. The researchers secured the following results:


-Perform a chi-square test by applying the 6 steps in of research hypothesis testing.

Step 1:
Step 2:
Step 3:
Step 4:
Step 5:
Step 6:

-Interpret the results in layman’s terms that a non-statistician would understand.
-How might the results obtained from the test affect the advertising strategy?

Fisher’s LSD approach and the posttest model

1. The Cordage Institute, based in Wayne, Pennsylvania, is an international association of manufacturers, producers, and resellers of cordage, rope, and twine. It is a not-for-profit corporation that reports on research concerning these products. Although natural fibers like manila, sisal, and cotton were once the predomonant rope materials, industrial synthetic fibers dominate the marketplace today, with most ropes made of nylon, polyester, or polypropylene. One of the principal traits of rope material is its breaking strength. A research project generated data giving the file entitled KNOTS. The data listed were gathered on 10 different days from 1/2″ diameter ropes.
a) Test to determine if inserting the day on which the testing was done was necessary. Use a significance level of
b) Based on the data gathered by the Cordage Institute, can it be concluded that there is a difference in the average
breaking strength of nylon, polyster, and polypropylene?
c) If you concluded that there was a difference in the average breaking strength of the rope material, use Fisher’s
LSD approach to determine which material has the highest breaking strength

2. When the world’s largest retailer, Walmart, decided to enter the grocery marketplace in a big way with its “Super Stores,” it changed the retail grocery landscape in a major way. The other major chains such as Albertsons have struggled to stay competative. In addition, regional discounters such as WINCO in the western United States have made it difficult for the traditional grocery chains. Recently, a study was conducted in which a “market basket” of producers was selected at random from those items offered in three stores in Boise, Idaho: Walmart, WINCO, and Albertsons. At issue was whether the mean prices at the three stores are equal or whether there is a difference in prices. The sample data are in the data filed called FOOD PRICE COMPARISONS. Using an alpha level equal to 0.05, test to determine whether the three stores have equal population mean prices. If you conclude that there are differences in the mean prices, perform the appropriate posttest to determine which stores have different means.

One-tailed test interpretations for three scenarios

Use the attached table to determine whether the correlations are significant and how you would interpret the results.

a. The correlation between speed and strength for 20 women is 0.567. Test these results at the 0.01 level using a one-tailed test.

b. The correlation between the number correct on a math test and the time it takes to complete the test is -0.45. Test whether this correlation is significant for 80 children at the 0.05 level of significance. Choose either a one-or two-tailed test and justify your choice.

c. The correlation between number of friends and grade point average (GPA) for 50 adolescents is 0.37. Is this significant at the 0.05 level for a two-tailed test?

Biostatistics: how to complete a research project and write a hypothesis about smoking

Based on the health promotion below, please tell me how to complete the research project and what hypothesis testing would be involved.

Health Promotion
A study is planned on the effects of a new health-education program promoting smoking cessation among heavy-smoking teenagers (20 cigarettes/equal to one pack per day). A randomized study is planned whereby 50 heavy-smoking teenagers in two schools (A and B) will receive an active intervention with group meetings run by trained psychologists according to an American Cancer Society protocol; 50 other heavy-smoking teenagers in two different schools (C and D) will receive pamphlets from the American Cancer Society promoting smoking cessation but will receive no active intervention by psychologists.

Random numbers are used to select two of the four schools to receive the active intervention and the remaining two schools to receive the control intervention. The intervention is planned to last for 1 year, after which study participants in all schools will provide self-reports of the number of cigarettes smoked, which will be confirmed by biochemical tests of urinary cotinine levels.

The main outcome variable is the change in the number of cigarettes smoked per day. A participant who completely stops smoking is scored as smoking 0 cigarettes per day. It is hypothesized that the effect of the intervention will be to reduce the mean number of cigarettes smoked by 5 cigarettes per day over 1 year for the active-intervention group. It is also hypothesized that teenagers in the control group will increase their cigarette consumption by an average of 2 cigarettes per day over 1 year.

Let us assume that the distribution of the number of cigarettes smoked per day at baseline in both groups is normal, with mean = 30 cigarettes per day and standard deviation = 5 cigarettes per day. Furthermore, it is expected, based on previous intervention studies, that the standard deviation of the number of cigarettes per day will increase to 7 cigarettes per day after 1 year. Finally, past data also suggest that the correlation coefficient between number of cigarettes smoked by the same person at baseline and 1 year will be 0.80.

Hypothesis Testing and Biostatistics

Part 1

7.109 Suppose we wish to test the hypothesis H0: μ = 2 vs. H1: μ ≠ 2. We find a two-sided p-value of .03 and a 95% CI for μ of (1.5, 4.0). Are these two results possibly compatible? Why or why not?

The mean ±1 sd of ln [calcium intake (mg)] among 25 females, 12 to 14 years of age, below the poverty level is 6.56 ± 0.64. Similarly, the mean ± 1 sd of ln [calcium intake (mg)] among 40 females, 12 to 14 years of age, above the poverty level is 6.80 ± 0.76.

8.3 What is the appropriate procedure to test for a significant difference in means between the two groups? 8.4 Implement the procedure in Problem 8.3 using the critical-value method.


8.5 What is the p-value corresponding to your answer to Problem 8.4?

8.6 Compute a 95% CI for the difference in means between the two groups.
An important hypothesis in hypertension research is that sodium restriction may lower blood pressure. However, it is difficult to achieve sodium restriction over the long term, and dietary counseling in a group setting is sometimes used to achieve this goal. The data on urinary sodium in Table 8.20 were obtained on 8 individuals enrolled in a sodium-restricted group. Data were collected at baseline
and after 1 week of dietary counseling
Table 8.20 Overnight sodium excretion (mEq/8hr) before and after dietary counseling

8.58 What are appropriate hypotheses to test whether dietary counseling is effective in reducing sodium intake over a 1-week period (as measured by overnight urinary sodium excretion)?

8.59 Conduct the test mentioned in Problem 8.58, and report a p-value.

8.60 Provide a 95% CI for the true mean change in overnight sodium excretion over a 1-week period.

A study was performed concerning risk factors for carotidartery stenosis (arterial narrowing) among 464 men born in 1914 and residing in the city of Malmö, Sweden [16]. The data reported for blood-glucose level are shown in Table 8.29.

Table 8.29 Comparison of blood-glucose level between men with and without stenosis

8.111 What test can be performed to assess whether there is a significant difference in mean blood-glucose level between men with and without stenosis? (Hint: F355,107,.95 =
1.307; F355,107,.975 = 1.377.)

8.112 Implement the test mentioned in Problem 8.111, and report a p-value (two-tailed).

PhoneEx Statistical Analysis

1.Provide an example of an experiment or data that has two factors. Provide details (what is being measured and the number of levels) of the levels for factor A and factor B.

2. PhoneEx provides call center services for many different companies. A large increase in its business has made it necessary to establish a new call center. Four cities are being considered – Little Rock, Wichita, Tulsa and Memphis. The new center will employ approximately 1500 workers and PhoneEx will transfer 75 people from its Omaha center to the new location. Once concern in the choice of where to locate the new center is the cost of housing for the new employees that will be moving there. To help determine whether significant housing cost differences exist across the competing sites, PhoneEx has asked a real estate broker in each city to randomly select a list of 33 homes between 5 and 15 years old and ranging in size between 1975 and 2235 square feet. The prices ( in dollars) that were recorded for each city are contained in the file called PhoneEx.

a) At the 0.05 level of significance, is there evidence to conclude that the average price of houses between 5 and 15 years old and ranging in size between 1975 and 2235 square feet is not the same in the house cities? Use the p-value approach.

b) At the 0-05 level of significance, is there a difference in average housing price between Wichita and Little Rock? Between Little Rock and Tulsa? Between Tulsa and Memphis?

c) Determine the sample size required to estimate the average housing price in Wichita to within $500 with a 95% confidence level. Assume that required parameters estimates are sufficient for this calculation.

Supporting Hypothesis Testing and Establishing Probabilities.

Discuss how the following supports hypothesis testing and establishing probabilities using the attached Excel chart.

1) The use and functionality of Excel software.

2) Review the report of the stats for the NCAA 2008 champions Kansas Jayhawks (basketball team). The hypothesis stated as “are the Jayhawks taller than the average NBA team” will result in some interesting discussion.

3) Run the data quickly and prove or disprove the hypothesis. This example like so many others may reveal unexpected outcomes. However, if you select teams like Indianapolis and run the same experiment you will get a different answer.

4) Discuss the reasons behind the “z” and “t” test. The player data is a population; this difference must be explained. Included in the data are some samples from the population that should be used as well.

Null & Alternative Hypotheses: Retail Prices

The R.R. Bowker Company of New York collects information on the retail prices of collectible children’s books and publishes its findings in Publisher’s Weekly. Last year, the mean retail of collectible children’s books was $35.44. A random sample of 40 collectible children’s books (published this year) is selected, the retail prices are noted, and the results are as follows:

Sample Size: 40
Sample Mean: $38.75
Sample Standard Deviation: $7.35

Does the sample data provide evidence to conclude that the mean retail price of collectible children’s books has increased over last year (using a= .10)? Use the hypothesis testing procedure outlined below.

a. Formulate the null and alternative hypotheses.
b. State the level of significance.
c. Find the critical value (or values), and clearly show the rejection and nonrejection regions.
d. Compute the test statistic.
e. Decide whether you can reject Ho and accept Ha or not.
f. Explain and interpret your conclusion in part e, What does this mean?
g. Determine the observed p-value for the hypothesis test and interpret this value. What does this mean?
h. Does this sample data provide evidence (with a=0.10), that the mean retail price of collectable children’s books has increased over last year?

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