Presenting correlation results using APA style. Use APA style to describe the following results from a correlation analysis.
Variable X: Weight of individuals
Variable Y: Height of individuals
r = 0.85
n = 100
p = .004
Please use appropriate language and symbols.
Presenting correlation results using APA style. Use APA style to describe the following results from a...
SPSS: Correlation Use SPSS or Excel to calculate the appropriate correlation coefficient for the following data for “Hours of Exercise” and “Life Satisfaction.” (0 = Not at all satisfied). Provide an APA-style results section write – up. (b) Graph the relationship. HINT: Below you will find instructions for the APA-style write-up. Complete the write-up on a word document and upload the file for submission. Hours of Exercise Life Satisfaction 2 6 0 2 5 13 6 15 1 3 2...
Compute the Pearson Correlation Coefficient, r, for the following data X Y 1 7 3 4 5 3 4 2 2 4 Note: If it is a decimal number with two or more than two places, leave only two decimal places after the decimal point and do not round. If it is a negative correlation, please do not forget to include the negative sign. 1a) The Pearson Correlation, r is: 1b) The correlation is Group of answer choices a) Medium...
please help me answer these questions based on the data Part 5: Correlation, Regression, and Goodness-of-fit test analysis. (20 pts) Using the midpoints as the x-variable and the frequencies as the y-variable of the different data sets of both groups of players, complete the following: I. Graph the scatterplot of points (x, y) to determine the outliers and influential points. Calculate the value for the Linear Correlation Coefficient (r) and give the interpretation. Using a significance level of 0.05, determine...
Use the following results to predict the following: a. The hip circumference of a man whose chest circumference is 95 centimeters. b. The height of a man whose forearm circumference is 28 centimeters. Styles 3. Use technology to find the regression line for each pair in Exercise 1 that has a strong correlation (chest, hip) Chest (cm) Hip (cm) Y X 93.6 98.7 95.8 99.2 93.1 94.5 99.6 104.1 92.1 93.9 96.6 102.5 101.9 97.3 104.5 107.S 92.7 95.3 Strong...
Linear Regression and Prediction perform a linear regression to determine the line-of-best fit. Use weight as your x (independent) variable and braking distance as your y (response) variable. Use four (4) places after the decimal in your answer. Sample size, n: 21 Degrees of freedom: 19 Correlation Results: Correlation coeff, r: 0.3513217 Critical r: ±0.4328579 P-value (two-tailed): 0.11837 Regression Results: Y= b0 + b1x: Y Intercept, b0: 125.308 Slope, b1: 0.0031873 Total Variation: 458.9524 Explained Variation: 56.6471 Unexplained Variation: 402.3053...
Section 5. Describing and Interpreting Results in APA Style 79. Interpreting Results Exercise: Sproesser, Schupp, and Renner (2014) 107 The researchers in this study were interested in how social situations can influence stress- induced eating. They grouped subjects according to self-reported stress-induced eating habits: consistently eating more (hyperphagics) or less (hypophagics) when stressed. Each subject was then exposed to one of three social situations: (1) a social inclusion condition in which subjects were told that a confederate partner had approved...
Regression and Correlation Methods: Correlation, ANOVA, and Least Squares This is another way of assessing the possible association between a normally distributed variable y and a categorical variable x. These techniques are special cases of linear regression methods. The purpose of the assignment is to demonstrate methods of regression and correlation analysis in which two different variables in the same sample are related. The following are three important statistics, or methodologies, for using correlation and regression: Pearson's correlation coefficient ANOVA...
8.The following results were obtained from a survey carried out by professor Socrates The survey followed a strict and rigorous protocol in order to ensure as much as possible the reliability of the results. It involved a random sample of twenty eight engineering students registered in an advanced professionally related subject. The variable X represents the number of hours a student devoted to the study of the subject under consideration during the academic year while Y represents the marks out...
Use the following convention table for R-square. From 0.0 to 0.2 Poor From 0.2 to 0.4 Decent From 0.4 to 0.6 Good From 0.6 to 0.85 Very Good From 0.85 to 1.0 Excellent Upload the ManBody data. Check which of the following four categories (BODYFAT, WEIGHT, HEIGHT, and KNEE) is the most correlated to AGE category. Make a scattered plot chart with X representing the most correlated category and Y representing the AGE, plot the line and compute the R-square....
Next, you decide to examine the relationship between patrol style and crime rates and find the following results using software. Please note that patrol style is dichotomous ( (x 1 if they use foot patrol, x 0 if they do not) - think about this as you interpret the results. %3D Coefficients Unstandardized Standardized Coefficients Coefficients Model Std. Error Beta Sig. (Constant) 35.090 3.274 10.717 .000 FootPatrol -18.860 4.630 .693 -4.073 .001 a. Dependent Variable: PropertyCrimeRate Write out this regession...