Category: Statistics

Will need to solve simple statistics problems ( no show work needed ) and user name and password would be given in chat .

Part 1
A principal wants to determine if a new ACT preparation program is effective. The data are contained in the schools.sav data file. Open the schools.sav file in SPSS. Use SPSS to determine whether a significant improvement existed between student performance on ACT tests in 1993 (act93) and ACT tests in 1994 (act94). Assume that the same students were involved in 1993 and 1994 testing. This requires a t-test. Review Chapter 10 of Using SPSS for Windows and Macintosh for information on paired t-tests as well as reporting, interpreting, and writing results using the APA format.
Create a report that answers the principal’s question. Write these conclusions in the APA format. Include your SPSS output to support your conclusion.
Part 2
A pharmaceutical company wants to determine whether there is a need for a new medication based on the data in the electric.sav file. Specifically, they want to determine whether a person is alive or dead 10 years after a coronary incident and whether that is reflected in a significant difference in the patients’ cholesterol levels (chol58) that were taken when the event occurred. Use chol58 as a dependent variable and VITAL10 as your independent variable. Address the following:
Analyze these conditions to determine whether there is a significant difference between the cholesterol levels (vital10) of those who are alive 10 years later compared to those who died within 10 years.
Include the SPSS output, which validates your conclusion.
Write a brief paragraph that describes your conclusions.
Refer to Unit 6 of Using SPSS for Windows and Macintosh for specific information about SPSS tests as well as interpreting and writing APA results. Pay attention to Levene’s test throughout to determine whether the assumption of equal variance was met when you make your final decisions about the analysis.
What conclusion did you reach? Write these conclusions in the APA format. Include your SPSS output to support that conclusion.
Part 3
Occasionally, you have 1 independent variable that has 3 or more levels or groups. For a parametric data set, an analysis of variance (ANOVA) is the proper calculation. Use ANOVA to address the following scenario:
A financial planner is interested in understanding the relationship between the dependent variable of the income level of respondents (rincdol) and the independent variable of their education level (ndegree) from the gss.sav data file. Use SPSS to complete the following:
Run an ANOVA to determine the overall conclusion.
Use the Bonferroni correction as a post-hoc analysis to determine the relationship of specific degree levels to income.
Explain the overall conclusions based on the analysis, and describe the relationship(s) between the levels of the degree earned and income.
Write your conclusion on the findings based upon the output using proper APA formatting.
Submit both the SPSS output file and your Word summary. Refer to Using SPSS for Windows and Macintosh’s section about a one-way ANOVA for information on how to interpret and write APA results.

Generate a Representative Sample of the Data
Analyze Your Sample
Generate Scatterplot
Observe patterns

please solve the following homework of finding the amount of people doing those professions in spain by region and municipality and the turnover of every profession. and provide the sources. the homework should be filled on the same excel I provided, with the most updated data available.

Complete a few assignments with 10 questions or less. Most of them were already completed as you would see the percentage.

the statistis refresher is the lab assignment read all directions carefully. the m johnson lab pdf is an answer sheet of another students that you can use to check your work with. the file with the slides has a question on the last slide it is a writing prompt. you must answer that question in a seperate page by itself.

Attached is the scope of the project (actividad32) and the project charter you must use mintab. An example is provided(Final Project Example) of how the information should look (    Measure   Pg 5 to Pg13  )
Determine or estimate using your project the following measurement bases:
1. For Takt Time, determine how much time the customer would expect for you to cook it.
2. For DPU (Defects Per Unit), determine the possible defects that may occur while cooking and create a table of defects per attempt to calculate the DPU. 
3. For Measurement Error, use simulation and determine. 
4. Implement the methodology of average and scope. 
5. Develop a frequency histogram.
6. Conduct an ANOVA (Analysis of Variance). 
7. Perform an R&R analysis (Repeatability and Reproducibility analysis). 
8. Process capability with Control Charts.

Instructions:
Data Review:
Begin by reviewing the data you have collected and presented in your contingency table. Ensure that the data is correctly organized and that the totals for each row and column are accurate.
State the Hypotheses:
Null Hypothesis (H₀): State that there is no association between the variables. (e.g., “There is no significant association between gender and preference for sports.”)
Alternative Hypothesis (H₁): State that there is an association between the variables. (e.g., “There is a significant association between gender and preference for sports.”)
Calculate Expected Frequencies:
For each cell in your contingency table, calculate the expected frequency using the formula:
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Record these expected frequencies in a new table.
Compute the Chi-Square Statistic:
Use the formula:
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Where X is the observed frequency, and E is the expected frequency for each cell in your table.
Sum the results for all cells to find the chi-square statistic.
Determine Degrees of Freedom:
Calculate the degrees of freedom for your test:
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Significance Level and Critical Value:
Choose a significance level (commonly Unknown node type: brUnknown node type: brα=0.05).
Using a chi-square distribution table, find the critical value corresponding to your degrees of freedom and significance level.
Decision Rule:
Compare your calculated chi-square statistic to the critical value from the chi-square distribution table.
If your chi-square statistic is greater than the critical value, reject the null hypothesis, indicating that there is a significant association between the variables.
If your chi-square statistic is less than or equal to the critical value, fail to reject the null hypothesis, indicating that there is no significant association between the variables.
Write a Conclusion:
Based on your results, write a conclusion that answers your original research question. Discuss the implications of your findings and any potential limitations of your analysis.
Submission Requirements:
A report containing all the steps outlined above, including your hypotheses, calculations, decision rule, and conclusion.
Attach the original contingency table along with the table of expected frequencies.
Evaluation Criteria:
Accuracy of calculations.
Clarity and logic in the explanation of steps and results.
Completeness of the report, including all necessary statistical components and a thoughtful conclusion.

How well do we know the world we live in? For a moment, imagine that there were only 100 people in the world. This exercise will allow you to understand how our world today is best represented. If the world were only a 100 people what would it look like? Pause for a moment and if possible jot down what comes to your mind as you think of this question. Now watch the video (at least until the first 1:40 seconds) “100 People- A World Portrait Links to an external site.”. Then review the detailed Statistics Links to an external site. of the data (updated in 2016) and read the rationale of how the data was collected Links to an external site.. These are some considerations that one needs to address whenever we intend to learn about global data!
There are two parts to the assignment:
Select “Start Assignment” and use text entry to describe how your impression of the world may (or may not) have changed. What were some of the data (list the topic and clearly mention the statistics) that you were most intrigued about and why (select at least two)? What were your pre-conceived notions on these data/topics? If there is one way you may contribute to better our world as seen through these data, what would you do? What were your thoughts on the data collection methodology? Word count – at least 350 . List the word count at the end.
Visit Mentimeter Links to an external site. to share data on one of the topics you have listed above. Make sure to report the specific statistics you shared above in your submission. Include your initials. Note – Mentimeter limits your submission to a few characters. Be brief.

Throughout the course, you have been exploring various concepts and building your skills in statistical analysis. In this final assessment, you will complete a data analysis report focused on analyzing correlations between a set of assigned variables.
Exploring the associations between some variables in the courseroom using correlations might provide some important information about learner success. You’ll need to pay attention to both magnitude, which is the strength of the association, and directionality, which is the direction (positive or negative) of the association. During this assessment, you’ll start learning about how to best approach correlational analyses like these and start getting some answers. You’ll explore the relationships that may or may not exist in your courseroom data.
INSTRUCTIONS:
Throughout the course, you have been exploring various concepts and building your skills in statistical analysis. This week, you will complete a data analysis report to analyze the correlation between assigned variables.
Exploring the associations between some variables in the courseroom using correlations might provide some important information about learner success. You’ll need to pay attention to both magnitude, which is the strength of the association, and directionality, which is the direction (positive or negative) of the association. During this assignment, you’ll start learning about how to best approach correlational analyses like these and start getting some answers. You’ll explore the relationships that may or may not exist in your courseroom data.
In this assignment, you’ll get a chance to run and interpret an inferential statistics analysis: correlations.
You will complete this assessment using the Data Analysis and Application Template [DOC] Download Data Analysis and Application Template [DOC](also known as the DAA Template).
The grades.jasp file is a sample data set. The data represent a teacher’s recording of student demographics and performance on quizzes and a final exam across three sections of the course. Each section consists of 35 students (N = 105). There are 21 variables in grades.jasp. This assignment is on correlations.
You will analyze the following variables in the grades.jasp data set:
Variables and Definitions
Variable Definition
Quiz 1 Quiz 1: Number of correct answers
GPA Previous grade point average
Total Total number of points earned in class
Final Final exam: Number of correct answers
The Data Analysis and Application Template has five sections:
The Data Analysis Plan.
Testing Assumptions.
Results and Interpretation.
Statistical Conclusions.
Application.
Step 1: The Data Analysis Plan
In Step 1:
Name the four variables used in this analysis and whether they are categorical or continuous.
State a research question, null hypothesis, and alternate hypothesis for one X-Y pair. For example, you could articulate a research question, null hypothesis, and alternate hypothesis for quiz1 (X) and final (Y).
Step 2: Testing Assumptions
Test for one of the assumptions of correlation—normality.
Create a descriptive statistics table to assess normality. This table should include the four variables named above.
Paste the table in the DAA Template.
Interpret the skewness and kurtosis values and how you determined whether the assumption of normality was met or violated.
Step 3: Results and Interpretation
In Step 3:
Paste the output of the intercorrelation matrix for all specified variables:
First, report the lowest magnitude correlation in the intercorrelation matrix, including degrees of freedom, correlation coefficient, p-value, and effect size. Interpret the effect size. Specify whether or not to reject the null hypothesis for this correlation.
Second, report the highest magnitude correlation in the intercorrelation matrix, including degrees of freedom, correlation coefficient, p-value, and effect size. Interpret the effect size. Specify whether or not to reject the null hypothesis for this correlation.
Third, report the correlation between GPA and final, including degrees of freedom, correlation coefficient, p-value, and effect size. Interpret the effect size. Analyze the correlation in terms of the null hypothesis.
Interpret statistical results against the null hypothesis, and state whether it is accepted or rejected.
Step 4: Statistical Conclusions
In Step 4:
Provide a brief summary of your analysis and the conclusions drawn.
Analyze the limitations of the statistical test.
Provide any possible alternate explanations for the findings and potential areas for future exploration.
Step 5: Application
In Step 5:
Analyze how you might use correlations in your field of study.
Name an independent variable and dependent variable that would work for such an analysis and why studying it may be important to the field or practice.
Submit your completed Data Analysis and Application Template as an attached Word document in the assessment area.