Correlation analysis

I know the answer for the following problem is:
r=0.62, df=8, not significant at .05
I am not sure how to get this answer. Please show all work.

An urban sociologist interested in neighborliness collected data for a sample od 10 adults on (x) how many years they have lived in their neighborhood and (y) how many neighbors they regarded as friends. Compute a Pearson’s correlation coefficient for this data and determine if the correlation is significant.

X Y
_________

1 1
5 4
6 2
1 3
8 5
2 1
5 2
9 6
4 7
2 0

Correlation analysis

I need to interpret the results of the attached linear regression analysis by writing a substantive response. The topic is: The number of home runs for a baseball team has no correlation to the number of wins.

The hypothesis of this linear aggression is:
H0: Number of home runs ≠ f(number of wins)
H1: Number of home runs = f(number of wins)

Correlation analysis

Share the practical applications of the study from the Unit 2 Individual Project. How would the results of this survey be used in the workplace?

Briefly describe correlational research. Name a variable from this study and one from the workplace that might prove to provide a correlational relationship and explain why you would choose these two? What did you learn about correlation and causation while completing the course?

Correlation Analysis

45. Five observations taken for two variables follow

X 4 6 11 3 16
i

Y 50 50 40 60 30
i

a. Develop a scatter diagram with x on the horizontal axis.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Compute and interpret the sample covariance.
d. Compute and interpret the sample correlation coefficient.

47. Nielsen Median Research provides two measures of the television viewing audience: a television program rating, which is the percentage of households with televisions watching a program, and a television program share, which is the percentage oh households watching a program among those with televisions in use. The following data show the Nielsen television ratings and share data for the Major League Baseball World Series over a nine-year period.

Ratings 19 17 17 14 16 12 15 12 13
Share 32 28 29 24 26 20 24 20 22

A. Develop a scatter diagram with rating on the horizontal axis.
B. What is the relationship between rating and share? Explain
C. Compute and interpret the sample covariance.
D. Compute the sample correlation coefficient. What does this value tell us about the relationship between rating and share?

Correlation analysis

(1) Draw a scatter plot and a quantile-quantile plot based on these two variables.
(2) Normalize the two variables based on z-score normalization.
(3) Calculate the correlation coefficient. Are these two variables positively or negatively correlated?

Correlation Analysis

Below are the height and width of 10 random books.

1) Is there a correlation between height and width?
2) If so, what is the correlation coefficient?
3) What is the equation of the correlation line?

10″ x 8″
8″ x 6″
6″ x 9″
12″x 15″
5″x”7
7″x10″
5.5″ x 8″
6″x 9″
7″ x10″

Correlation analysis

Student Admissions
Admissions want to investigate alternate means of determining who will be admitted to their university as freshmen. The admissions counselors determine that one of the best predictors of undergraduate grade point average (GPA) is a student’s high school GPA. They compile information through their databases about their high school GPA and their freshmen year GPA for all students admitted to the university in the past five years. After running the data through a program, they are determined to find out if the predictive ability of the high school GPA is accurate.

Correlation Analysis

See the attached file.

o Formulate both a numerical and verbal hypothesis statement regarding your research issue.

o Perform the five-step hypothesis test on data pertaining to your selection.

o Describe the results of your test, and explain how the findings from this hypothesis testing can be used to answer your research question.

o Include your raw data tables and the results of your computations in your paper, using both graphical and tabular methods of displaying data and results. (***THIS IS VERY IMPORTANT TO SHOW***)

Correlation analysis

6.1
The goal of this study is to determine the strength and direction of the age, height, and weight variables in correlation with the FVC measure in the population.

There were 31 variables measured on 800 elderly subjects. Variables include selected demographics (age, gender, race); selected anthropometrics (height, waist circumference, hip circumference, and body mass index); smoking history (status and pack-years for current or former smokers); and disease history (history of emphysema, bronchitis, asthma, pneumonia, CHD, diabetes).

A bivariate correlation analysis was conducted to test the assumption that there is a linear relationship between variables. The age and height variables were compared to the Forced Vital capacity (FVC) by viewing scatterplots. Analysis of scatterplots indicated that the data points for age verses FVC have a weak negative association. The scatterplot for height verses FVC indicated a moderate positive association.

A further measure of correlation was conducted on the age, weight, height, and FVC variables using the Pearson product-moment correlation (Pearson’s r). Per the Pearson correlation, the age variable had a weak negative association with FVC (r = -.172, (df = 798), p < .001, CI =-.238, .104) and the height variable had a moderate positive association with FVC (r=.683, (df=798) p < .001, CI = .644,.718). The weight variable had a weak positive correlation to FVC (r= .331, (df = 798), p<.001, CI = .268,.391).

Using a point biserial correlation to account for the nominal variables, the race variable showed a negative correlation to FVC (r= -.156, (df=798), p< .001) and the gender variable showed a moderately strong correlation to FVC (r= .619, (df=798), p< .001).

See attached file for full problem description.

Correlation analysis

A study was conducted to determine if there was a relationship between A study was conducted to determine if there was a relationship between the prices a non-member of a club paid for various publications and the prices that a member paid for the same publications. The data collected is shown below.
Non-member Member
Price, x Price, y
58 32
42 22
46 20
32 16
25 19
75 58
35 34
63 48

Find the value of E x^2 (note E stands for the Summation Notation)

A) 93,624 B) 19,712 C) 9349 D) 13,251

Correlation analysis

In these two exercises, construct a scatter plot, find the value of the linear correlation coefficient r, find the critical value of r from Table A-6 by using &#945; = 0.05, and determine whether there is a linear correlation between the two variables.

Song Audiences and Sales The table below lists the numbers of audience impressions (in hundreds of millions) listening to songs and the corresponding numbers of albums sold (in hundreds of thousands). The number of audience impressions is a count of the number of times people have heard the song. The table is based on data from USA Today. Does it appear that album sales are affected very strongly by the number of audience impressions?
Audience impressions 28 13 14 24 20 18 14 24 17
Albums sold 19 7 7 20 6 4 5 25 12

State Budget and Days Late New York State has become notorious for approving the state budget after the annual deadline of April 1. The amount of the budget (in billions of dollars adjusted for inflation) and the number of days late are listed below with corresponding entries representing the same year. (The data are in order by row.) Does it appear that the size of the budget affects the number of days that the budget is late? Use a 0.05 significance level.

Budget
101 96 91 85 80 73 71 66 63 63
62 58 55 52 49 46 44 40 37 35

Number of Days Late
133 44 45 124 34 125 13 125 103 67
68 4 1 64 48 18 19 10 4 4

Correlation analysis

The following data refers to gross earned income, in thousands of dollars per year, and level of taxation on that income. Determine whether a relation exists between these two factors, and if so its strength, then predict how much tax any other
individual would have to pay in this mythical society.

INCOME 7 9 10 13 18 18 20 24 36 45
% TAX 2 4 4 7 10 13 15 12 13 20.

Correlation Analysis

Biomechanics of ligament and relationship between age, diagnosis and histology.

The aims were to determine whether there is a link between histology. That is SMA, EVG and MT and the other parameters. And a link between the histological parameters in themselves.

Hypothesis: young’s modulus and/or yield and/or strain is related to age/diagnosis/histology

The samples are from ligaments removed from patients after surgery.

Patient number Age Diagnosis Duration of symptoms (months) EVG mt SMA strain Yield Youngs
1 28 Prolapse 6 0.7097 0.1178 82 63.32 1.51 0..067
2 48 Stenosis 84 0.6473 0.0978 26 177 4.55 0.051
3 80 Stenosis 144 0.6785 0.1301 19 105.01 1.4 0.021
4 68 Stenosis 36 0.6329 0.085 17
5 26 Prolapse 27
6 69 Stenosis 48 0.438 0.3909 9 205.29 6.41 0.058
7 36 Prolapse 42 0.6228 0.2268 71 161.67 1.68 0.0327
8 33 Prolapse 18 0.7498 0.1781 72 159.17 1.68 0.021
9 38 Stenosis 96 0.6397 0.2527 76
10 24 Prolapse 12 0.6999 0.134 63

1. is there a correlation between age and any of the other variables

2. is there a correlation between diagnosis and any of the other variables

3. is there a correlation between EVG,SMA or MT independent of other factors

4. Is there a correlation between the strain, yield or youngs and any of the MT, EVG and SMA

5. Is there a correlatin between youngs, yield and strain and age or diagnosis

6. Is there a correlation between duration of symptoms and SMA irrespective of other factors