Define and provide examples of:
-Basic probability
– Bayes theorem
– Multiplication rule
– Addition rule
-Binomial distribution
-Poisson distribution
-Normal distribution
-Sample distribution
-Central limit theorem
Use Apa Style, cites, references and avoid plagiarism.
DO YOU HAVE ACCESS OR CAN YOU GET ACCESS TO THESE,
Field, A. P. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Los Angeles, CA: Sage. ISBN: 9781526436566.
IBM SPSS Statistics Standard GradPack 25 for Windows (06-Mo Rental is satisfactory)
ANCOVA Analysis
A recent study of driving behavior suggests that self-reported measures of high driving skills and low ratings of safety skills create a dangerous combination (Note: those who rate themselves as highly skilled drivers are probably overly confident). Drivers were classified as high or low in self-rate skill based on responses to a driver-skill inventory, then classified as high or low in safety skill based on responses to a driver-aggression scale. An overall measure of driving risk was obtained by combining several variables such as number of accidents, tickets, tendency to speed, and tendency to pass other cars. Enter the following data into SPSS and use anANCOVA to analyze the results.
Self-Rated Driving Skill
Low
High
Driving Safety
Low
6
5
6
3
6
4
5
6
3
2
3
4
3
5
4
1
High
3
4
4
3
3
2
4
5
8
9
9
7
8
9
7
9
1. State the independent variables (factors) and dependent variable in this study. 2. What are the mean driving risk scores for each group? 3. State the null and alternative hypotheses for the ANCOVA. 4. State the numerical results for the ANCOVA (include F, df, p, and 2) and state the statistical decision. 5. Write a paragraph as in a journal article that summarizes and interprets the results of the ANCOVA for this study on driving risk.
MANOVA Analysis
Researchers are interested in the effects of cognitive behavior therapy and behavior therapy on Obsessive Compulsive Disorder. We could compare a group of OCD sufferers after CBT and after behavior therapy with a group of OCD sufferers who are still awaiting treatment (a no treatment condition).
As OCD has both cognitive and behavioral elements, it is not enough to look only at therapy’s influence on behavioral outcomes. Therefore, our study used two dependent measures: the occurrence of obsession-related behaviors (Actions) and the occurrence of obsession-related cognitions (Thoughts).
The dependent variables were measured on a single day and so represent the number of obsession-related behaviors/thoughts in a normal day. Use data set OCD.sav.
1. What is/are our research question(s)?
2. Prescreen the data. a. Does our data meet all the assumptions for a MANOVA?
b. Does the data need to be corrected for outliers and normality? (Copy and paste in to this section the information that helped you reach your conclusion).
c. Does the data demonstrate homogeneity of variance-covariance? (Copy and paste in to this section the information that helped you reach your conclusion).
3. “Run” the MANOVA analysis (i.e., use the printout of SPSS output). a. Which MANOVA test statistic should you use? Why?
4. Using the appropriate group multivariate statistics and ANOVA/post hoc tests, report your results.
Information about test norms allows you to equate scores across different tests of the same construct and lets you compare individuals to each other. Once you have the standard deviation of a score, you can calculate an individuals z-score. Z-scores, also known as standard scores, tell you how many standard deviations away from the mean an individual is. Scores that are two standard deviations away from the mean represent the most extreme 5% of the population and often are considered to be unusual enough to warrant special consideration, such as a clinical diagnosis. For instance, IQ scores that are two standard deviations above the mean (130 or greater) are considered in a gifted range and scores two standard deviations below the mean (70 or lower) are considered intellectually deficient. Scores on measures of depression that are two standard deviations above the mean often are considered to represent clinical depression.
T-scores are another kind of standard score; the MMPI is the best known example of a test that uses T-scores. (Note that T-scores have nothing to do with t-tests.) Z-scores have a mean of 0 and a standard deviation of 1; T-scores have a mean of 50 and a standard deviation of 10. Thus, the average score on a test would be assigned a T-score of 50 and a z-score of zero. A score that was one standard deviation below average would be assigned a T-score of 40 and a z-score of -1.
For this Knowledge Assessment, you consider how raw test scores can be converted into more meaningful standardized scores, allowing you to meaningfully compare tests and to compare individuals.
In the provided dataset, you previously created a Risk-Taking scale by adding items R1 through R6.
Note: Please refer to the following image to complete question #3.
Multiple AttemptsNot allowed. This test can only be taken once.Force CompletionThis test can be saved and resumed later.
Question Completion Status:2.5 points
2.5 points
2.5 points
For this Knowledge Assessment, you calculate the concurrent validity coefficient between a predictor scale and criterion measure in the dataset provided. First, you will be guided through the process of how to create new variable scales. Then, you calculate the validity measure on one of the scales.
The MoneyData.sav dataset that you have been provided contains three scales that measure financial attitudes:
LIFESTYLE (L1 to L6) measures the desire for a luxurious lifestyle
DEPENDENCE (D1 to D6) measures the tendency to depend on others for financial support (high scores) vs. supporting others (low scores)
RISKTAKING (R1 to R6) measures the tendency to take financial risks in investments and careers
Create Three New Variables Showing the Scores on These Three Scales
To create the RISKTAKING scale, click on TRANSFORM>COMPUTE VARIABLE. In the Target Variable field, type RISKTAKING. In the Numeric Expression field, type SUM(R1 TO R6).
To create the DEPENDENCE scale, click on TRANSFORM>COMPUTE VARIABLE. In the Target Variable field, type DEPENDENCE. In the Numeric Expression field, type SUM(D1 TO D6).
On the LIFESTYLE items, item L6 (Id rather have a modest lifestyle because it is less stressful) is scored in the reverse direction from the other items. People endorsing this item want a less extravagant lifestyle; endorsing the other items suggests the desire for a more extravagant lifestyle. The scoring on this item needs to be reversed. To create the reversed L6 item, click on TRANSFORM>COMPUTE VARIABLE. In the Target Variable field, type L6R. In the Numeric Expression field, type 6 L6. By subtracting the item responses from six, they are reversed: 5 becomes 1, 4 becomes 2, etc. To create the LIFESTYLE scale, click on TRANSFORM>COMPUTE VARIABLE. In the Target Variable field, type LIFESTYLE. In the Numeric Expression field, type SUM(L1 TO L5, L6R).
Calculate a Validity Measure for One of the Scales
There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = – .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale.
Think of another relationship that might support the validity of one of the scales, and then test your hypothesis using the data. You will need to submit:
Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported.
The results of your statistical test of your validity hypothesis.
Your conclusion about validity given the results of your statistical test.
PLEASE ANSWER THE 3 QUESITONS with this data”
3.33 points
3.33 points
.3.34
Total of 9 questions.
Table #2.2.10: Data of Median Income for Females
$31,862
$40,550
$36,048
$30,752
$41,817
$40,236
$47,476
$40,500
$60,332
$33,823
$35,438
$37,242
$31,238
$39,150
$34,023
$33,745
$33,269
$32,684
$31,844
$34,599
$48,748
$46,185
$36,931
$40,416
$29,548
$33,865
$31,067
$33,424
$35,484
$41,021
$47,155
$32,316
$42,113
$33,459
$32,462
$35,746
$31,274
$36,027
$37,089
$22,117
$41,412
$31,330
$31,329
$33,184
$35,301
$32,843
$38,177
$40,969
$40,993
$29,688
$35,890
$34,381
2.2.6
Create a histogram and relative frequency histogram for the data in table #2.2.10. Describe the shape and any findings you can from the graph.
a) Why are the measures of central tendency along with the measures of variation considered to be sufficient, when describing the characteristics of a product or a process? Provide examples that support your answer
b) What is the difference between standard deviation and variance? Explain your rationale
The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care costs and best practices. To be effective in evaluating and interpreting research, the reader must first understand how to interpret the findings. You will practice article analysis in Topics 2, 3, and 5.
For this assignment:
Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the Topic Materials or textbook. Complete an article analysis for each using the “Article Analysis 1” template.
Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 1,” for an example of an article analysis.
While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. Refer to the for assistance.
Descriptive Statistics Analysis
Describe the Sun Coast data using the descriptive statistics tools discussed in the unit lesson. Establish whether assumptions are met to use parametric statistical procedures. Repeat the tasks below for each tab in the Sun Coast research study data set. Utilize the Unit IV Scholarly Activity template here.
You will utilize Microsoft Excel ToolPak. The links to the ToolPak are here in the Course Project Guidance document.
Here are some of the items you will cover.
The title and reference pages do not count toward the page requirement for this assignment. This assignment should be no less than five pages in length, follow APA-style formatting and guidelines, and use references and citations as necessary.
ue in 12hours
Correlation and Regression Analysis Using Sun Coast Data Set
Using the Sun Coast data set, perform a correlation analysis, simple regression analysis, and multiple regression analysis, and interpret the results.
Please follow the Unit V Scholarly Activity template here to complete your assignment.
You will utilize Microsoft Excel ToolPak for this assignment.
Example:
The title and reference pages do not count toward the page requirement for this assignment. This assignment should be no less than two pages in length, follow APA-style formatting and guidelines, and use references and citations as necessary.
