Regression Between Male Height, Age And Weight Essay

3- How would you make it an experimental (rather than correlational) study (it might help to be specific here as well and define the two types of studies in your

The Barbie Bungee lab was conducted in order to find the association between the amount of rubber bands and the distance the Barbie bungeed. Before performing the final experiment, the group conducted an initial investigation to get data that could be analyzed to examine the comparison from the amount of rubber bands to the length Barbie was able to bungee. In the investigation rubber bands would gradually be added one by one starting at two rubber bands. Each time a rubber band was added, three trial bungees were done and the lengths the barbie dropped were recorded. Using data collected from our background investigation, the group used excel to create a sheet displaying the data in a table, a graph showing the correlation constant, the line of best fit. The line of best fit was in slope-intercept form (y=mx+b) where y represents the length of the trial average; m represents the slope

1. Dependent Variable HR, SV, BP 2. Independent Variable level of activity 3. Controlled Variables age, gender

Assuming the variables used to test linear regression were continuous, had a linear relationship, had no significant outliers, showed homoscedasticity as well as independence of observations, we tested a series of bivariate regressions to explain whether or not there was a statistically significant portion of variability in the dependent variable from variability in the independent

Iterations of analysis eliminated data points that were listed as “unusual observations,” or any data point with a large standardized residual. After 5 iterations, the analysis showed improved residual plots. Randomness in the versus fits and versus order plots means that the linear regression model is appropriate for the data; a straight line in the normal probability plot illustrates the linearity of the data, and a bell shaped curve in the histogram illustrates the normality of the data.

University of Texas-Houston Health Science Center . (2013). Hypothesis Testing . Retrieved March 21, 2013, from Biostatistics for the Clinician : http://www.uth.tmc.edu/uth_orgs/educ_dev/oser/L2_2.HTM

Information about statistical significance and confidence interval is presented and reviewed. There was good use of tables and figures that included titles and headings that were clearly and appropriately labeled. The results were also clearly displayed in tables with identifiable titles and labeled headings. The study included descriptive statistics. The study described the main characteristics in the dataset. The mean and standard deviation for each blood pressure measurement was calculated before and after crossing of the legs was performed by the study subjects. Inferential statistics were also present in this study. In order to test mean differences with three or more groups, an analysis of variance (ANOVA) statistical test is used. This research study conducted a repeated-measure ANOVA, which is when there are three or more measures of the same dependent variable

A researcher found a significant relationship between a person's age, a, the number of hours a person works per week, b, and the number of accidents, y, the person has per year. The relationship can be represented by the multiple regression equation y = -3.2 + 0.012a + 0.23b. Predict the number of accidents per year (to the nearest whole number) for a person whose age is 42 and who works 46 hours per week.

7. This practice problem uses the data contained in the file named Ch. 3 Data Set 3. There are two variables in this data set. The data sets can be found through the Sage Materials in the Student Textbook Resource Access link, listed under Academic Resources. Using IBM® SPSS® software, compute all of the measures of variability you can for height and weight. Copy and paste the output from IBM® SPSS® into this worksheet.

Therefore, not fitting with what the hypothesis states. 5c. What could be changed and improved for the correlation technique would be what studies they receive their data from. The correlation technique cannot be manipulated and it is used with the existent data. By changing the data the answers could be changed in order to prove the hypothesis without any defaults. 5d. Correlations are great when it comes to comparing variables. By using the correlation method, it cannot be manipulated because it is using the information that already exist. But, by using an experiment a person can actually prove the hypothesis and it is more concise. It can be manipulated meaning that a person can always find the reason for the results. Furthermore, this can conclude whether the independent variable affected the other variables in the experiment. 5e. An experiment that would help support the hypothesis is by giving 2 people with split brain and 2 people with the intact brain a task that would exercise the brain to see the relationships of the functions of the left and right hemispheres. The experiment would be showing a slide with the faces of well-known celebrities and using name tags. The people with the intact

"There are several different kinds of relationships between variables. Before drawing a conclusion, you should first understand how one variable changes with the other. This means you need to establish how the variables are related - is the relationship linear or quadratic or inverse or logarithmic or something else" ("Relationship Between Variables ", n.d)

(TCO 3) Before performing linear regression, it is important to ensure that a linear relationship exists between the dependent and independent variables by plotting observed

Text: Daniel, W. W. (2009). Biostatistics: A Foundation for Analysis in the Health Sciences, 9th edition. NY: John Wiley & Sons.

The scientific question of the project was, Does the size of a tire affect the bike’s speed? The hypothesis was , If the smaller tires were used, then the bike would go faster. The important procedures were: Make sure all equipment is ready. Test the standard wheel of 1 rotation or pedal a second to ride to the finish line. Test smaller and bigger wheels. Record data and have at least 3 trials. Record the data on a piece of paper and compare results to your hypothesis. The Independent variable is the size of the wheel on the bike. The Dependent variable is the standard wheel or tire on the bike. The control group was the bike’s speed and the standard wheel or tire. The Experimental group is the other tires or wheels being tested on the bike. The control variables were the rate of pedaling , the same bike model was used, and the same distance for

| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are