Description The Steps to Take: When you have chosen your ORDINAL variable: Gather the frequency distribution for your variable and be sure you are using the numbers for the 2022 survey year. You will use the frequency distribution to find the mode, median, and range, when relevant. Remember to ignore any category that is for a "non" answer, e.g., don't know, no answer, no response, etc. Be sure to note the names of the categories - they may be coded with numbers but those do not mean anything - use the names for each category! Analyze only your ORDINAL variable in this part, and discuss it just like we've been doing in the worksheet, homework, and discussion, for central tendency and variability. If you would like more guidance on how to choose and deal with your variables, check out the examples tab. Use the outline to write up your analysis. Type up your paper in whatever program you use for that, e.g., Word, Google Docs, etc.. Save it often if the program doesn't do that for you. (Back up is good!) Look at the rubric and refer to it when you edit your draft - it shows you what is expected in each section (just like the outline!). There is no great need to include the frequency distributions - but if you do want to include them, put them in an appendix (optional). Visit the Writing Center (virtually or in person) with a draft and get their feedback on what can be better. Edit accordingly. After you have edited it (at least three times), 'save as' or 'print to' a PDF file format. That file is what you will submit for this assignment. Submit your file here. Don't forget to do the other two Parts. After you have submitted and I have reviewed it, please read my comments. Let's talk about how it went. It will be marked complete if you have a paragraph describing your appropriate central tendency and variability statistical patterns for your variable in your own words. If it is marked incomplete and you turned it in on time, we will have time to do a re-submission, if you wish. Use this Outline: Ordinal Variable– Describe the distribution of your data for this variable. Interpret the frequency distribution and appropriate measure(s) of central tendency (Mode, Median) and variability (Range). Introduction - Tell us what your variable is, in everyday words and, briefly, why you chose it. Description of the statistical patterns of central tendency and variability, in everyday words. Use ONLY the relevant statistics for the level of measurement. OPTIONAL - Appendix with frequency distributions and/or the work done to get the the statistics you used.
Description TC Ice Cream Excel Workbook: Submit the TC Ice Cream Excel Workbook.xlsx. For this assignment, work should be completed in the Flavor One Bivariate Analysis, Flavor Two Bivariate Analysis, Flavor One Multi. Analysis, and Flavor Two Multi. Analysis worksheets. Do not remove any sheets from the workbook. PowerPoint Presentation: Submit a PowerPoint presentation using the Milestone Two PowerPoint Template. Any sources should be cited in APA format. Consult the Shapiro Library APA Style Guide for more information on citations.
Description You are working for Rishe Solutions Incorporated, a 14,000 person consulting organization. You work in a 600-person division of the organization that provides client services in your field. That is, all the types of professional work products your field produces are marketed to Rishe clients as consulting services. Your manager has asked you to write a memorandum to be provided to your division leaders. This memorandum will make a case that increasing the number of employees in the division proficient in statistics and probability will make the division more profitable. The profitability will emerge from improving provided services' quality and improving division effectiveness and efficiency. You will recommend that this be accomplished by making data literacy a requirement for all new hires. The leaders she has asked you to address the memorandum to are Verena Bonet, Vice President of [your field]; Amara Nwafor, Associate Vice President of [your field]; and Elliott Richdale, Human Resources Director for [your field]. You will also copy it to your manager, Dianne Reeves. You are to assume that these leaders are senior professionals in your field with the knowledge that entails. Specifically, Ms. Reeves is requesting that the division require and verify probability and statistics proficiency for all new hires in the division. She has tasked you with accomplishing this policy change request by: Highlighting how statistics and probability are used in the services your division provides to clients. To support your argument, this part of the document will summarize aspects of the services your division provides in which statistics and probability are applied and for what purpose each is used. Note: In this section, I expect you to use the research you did for assignment IDL 1. However, as you are writing to a different audience for a different purpose, you will use it differently. If you feel your research from IDL 1 is inadequate for this assignment, you may add additional sources. Documenting the importance to division success of having all employees engaged in data analytics (analyzing data using probability and statistics for increased profitability and meeting division goals). For this part of the work, she is providing you with a document summarizing external research data provided by a Rishe partner, Deloitte, to support this case. She wants you to review this data for: Relevance: Is the data Deloitte collected relevant to Rishe? Are the participants from whom Deloitte collected the data similar enough to Rishe to suggest their findings would be applicable to Rishe? You will include what the data indicates, the source of the data provided, the size and reliability of the study, and how that data source aligns or not with Rishe as an organization. How does it support the claim you are making? How the data provided can support your argument that more data literate/probability and statistics proficient employees will make the division more profitable. After reviewing the data, you will use them to make the case that your division will be more profitable if more employees are able to engage in data analytics (that is applying probability and statistics knowledge.) You will recommend that the organization accomplish this by making data literacy a requirement for all new hires in the division.
Description Step 1: Your instructor will provide you with 10 values to use for this lab. Gather 10 MORE of your own to add to the 10 provided by your instructor. Do the following: Survey or measure 10 people to find their heights. Determine the mean and standard deviation for the 20 values by using the Week 3 Excel spreadsheet. Post a screen shot of the portion of the spreadsheet that helped you determine these values. How does your height compare to the mean (average) height of the 20 values? Is your height taller, shorter, or the same as the mean of the sample? Note: The following image is just an example. They are NOT the values you should be using for your lab. Your instructor should have sent you our data values for your Week 5 Lab. Please reach out to your instructor if you do not have your data values. Data Example of 10 people with different heights(your spreadsheet will have 20 values—10 from your instructor and 10 from your own data gathering). Step 2: Give some background information on the group of people you used in your study. You might consider using the following questions to guide your answer. How did you choose the participants for your study? What was the sampling method: systematic, convenience, cluster, stratified, simple random? What part of the country did your study take place in? What are the age ranges of your participants? How many of each gender did you have in your study? What are other interesting factors about your group? Step 3: Use the Week 5 Excel spreadsheet for the following. (Use the Empirical Rule tab from the spreadsheet). Determine the 68%, 95%, and 99.7% values of the Empirical Rule in terms of the 20 heights in your height study. What do these values tell you? Post a screen shot of your work from the Week 5 Excel spreadsheet. (Use the normal probability tab from the spreadsheet). Based on your study results, what percent of the study participants are shorter than you? What percent are taller than you? Post a screen shot of your work from the Week 5 Excel spreadsheet
Description A social work intern is conducting a parenting class for clients at her agency. The social work intern is interested in examining if there is a relationship between participants’ level of education (measured by how many years of schooling completed) and participants’ training posttest scores. The student ran a Pearson’s correlation to address the research question. The intern's data file is attached. Focus on the relevant variables: “Level of Education” and “Posttest skill scores”. For this homework, do the following: State your research question State your independent and dependent variables State your research hypothesis State your null hypothesis Conduct a Pearson's correlation in JASP with the intern data. Here is how to do it (details are in this week's PowerPoints): Create a spreadsheet with the intern data so that you can run it in JASP Save your file as .csv If using JASP online: Upload file to OSF Open your file in JASP: Open > My Computer > [Your file] If using JASP online: Open > OSF > Log in to OSF > [Your file] Double check that the variables are measured at the correct levels Run descriptives Run a graph Run your Pearson's correlation Interpret output; be sure to report: Your descriptives output table Write one - two sentences describing each of the variables Your graphs Your Pearson's correlation test output table Write an explanation of your Pearson's correlation test results in sentence form. Use this format, and fill in the information in red based on your results: I ran a Pearson's correlation test in JASP to examine [insert a brief explanation of what you were trying to understand]. I set the alpha level to ___. Results show that there was/was not a [if applicable: small/medium/strong] [if applicable: positive/negative] significant ______ between education and posttest scores, where p=___, r = ____. Therefore, I reject/do not reject the null hypothesis. In summary, [in simple terms, what does this mean about relationship between the variables?]
Description QUALITATIVE RESEARCH WORKSHOP: WEEK 5 Consider the following question: Is interview data an appropriate choice for your study? In-depth and semi-structured interviews explore the experiences of participants and the meanings the participants attribute to those experiences. Researchers encourage participants to talk about issues pertinent to the research question by asking open-ended questions, usually in one-on-one interviews. The interviewer might re-word, re-order, or clarify questions to further investigate topics the respondent introduces. The data collection method of interviewing is a good choice when the researcher wants to spend time with people who have experienced the phenomenon of interest, has the intent to listen to detailed stories and experiences, and is receptive to new or discrepant ideas and stories that may vary from the original plan of the study. However, this method requires access to participants who are able and willing to share their thoughts. This labor-intensive process of recruiting, scheduling, interviewing, and transcribing requires initiative, persistence, and the ability to spend time with people you do not know. For your Workshop this week, you will consider the application of this strategy to your study. BY DAY 3 In this week’s Workshop, visit your unique thread and post responses to the following: What is the current version of your research question? Reflect on the choice of interviewing as the data collection method for addressing your proposed study. Why might you choose interviewing over other qualitative data collection techniques (e.g., focus groups, observational data collection)? Consider the kinds of questions you would like to ask. Are they personal? Embarrassing? Might they put your participants at risk? Provide some examples of the kinds of questions you would like to ask. Identify one or more possible ethical considerations given the types of questions you would like to ask. For example, if you are asking someone to reflect on his or her experience as a drug addict, perhaps that person will reveal stories about hurting loved ones or breaking the law. How might you handle this?
Description Appendix #1. Instructions for Data Analysis Project (first part) In this first step of your data analysis project, you are expected to submit a proposal of no more than 3 pages (double space, 12 Times New Roman, and 1 inch margins, including tables and figures). You need to include the following elements in your proposal: (1) your research question; (2) why it is of your interest; (3) your data source; and (4) a brief summary descriptive of the variables you will use in the t-test or regression or both. [If you cannot find your own data, you can use the General Social Survey 2014 (GSS 2014.sav) dataset posted on Canvas] Research question State clearly your research question and explain why it is of your interest. Describe your data sources. Brief descriptions of data: data source (firsthand or second hand; where did you get it, if second hand), year of collection, unit of analysis, sample size, etc. Descriptive Statistics (Creating the “Table 1”) You will create a table that provides descriptive statistics of variables that you plan to use in your t-test/regression. In many journal articles, authors present this information as “Table I” (because it is most likely the first table presented in their papers) with table titles such as “Descriptive Statistics” or “Sample Characteristics.” For continuous variables, present means and standard deviations (sometimes, minimum and maximum are also presented). For nominal variables (dichotomous or categorical variables), present frequency percentages or proportions rather than means or standard deviations. For example, it makes no sense to calculate the mean or standard deviation of race as a nominal variable.
Description Review the Learning Resources about the various approaches that can be used to demonstrate the validity of a psychological measure. Pay particular attention to the concept of construct validity and the various ways the Learning Resources address this idea. Consider the construct you are going to measure and whether you would focus on face validity. Also, think of a couple of ways you can demonstrate construct validity for your measure. Identify any additional validity approaches you would use for your measure. Submit a that addresses the following: Summarize the different approaches for evaluating the validity of an assessment or measure. In your summary, include a definition and explanation of the following validity concepts: face validity, construct validity and the various ways to demonstrate construct validity (e.g., correlations with criterion measures, confirmatory factor analysis, etc.), and criterion-related or predictive validity.
Description About: In this discussion board, let's help each other understand a fundamental concepts covered in the first five modules of our course and related textbook material, video lesson, and lesson notes. We'll explore levels of measurement, types of variables, research questions, and various statistical measures. Please choose ONE (1) concept from the list below and provide a detailed explanation: Levels of Measurement: Nominal, Ordinal, Interval, Ratio scales - Explain each level and provide examples of variables that fall under each level. Variables: Define independent and dependent variables, and provide examples of each in a research context. Graphs: Discuss which level of measurement goes with each graph (line graph, histogram, pie chart, bar graphs) Measures of Central Tendency: Explain mean, median, and mode, and discuss when each measure is appropriate to use. Explain what level of measurement corresponds to each measure. Measures of Variability: Discuss range, variance, and standard deviation, and explain their importance in analyzing data. Rates and Percentages: Define rates and percentages and provide examples of how they are used in research and everyday contexts. Skewed Distributions: Explain the difference between a positive or negatively skewed distribution. Provide an example Choose your own! Explain a concept not listed here but that you think you would do a great job explaining. Replies: Reply to at least two students with feedback on their explanations offering advise for clarity and thoroughness if needed, feel free to add additional details and explanations as well as an additional application or example.
Description Benford's Law Benford's Law isn't actually a statistical principle, but it has significant statistical components, implications, and rationale. Conduct some basic research into this law and consider some situations in which engineering might deal with naturally occurring datasets that could be evaluated or described using it. Think about what you've learned about probability and how it can help explain why data behaves as described by Benford. Write and submit an essay that uses the principles of probability covered in this class to explain the basic observations enabled by Benford's Law. Offer some suggestions for how Benford's Law might be useful in one or more engineering situations, and why you think so. (Hint: Think in terms of an engineering application where you might want to validate that arriving data is real.) To earn credit with this assignment, the submitted essay must be well-written, original, cleanly presented, and offer a complete discussion of the topic. It should be engagingly written at a serious junior undergraduate academic level. Every year I reject one or two.
