Category: Statistics

The subject area is: Data Analytics Background to the task:
IBM is a large sof

The subject area is: Data Analytics Background to the task:
IBM is a large software and hardware vendor, with a focus on AI and Quantum. Part of IBM’s strategy is to support the skilling up to 30 million people by 2030, in order to cater to the changing needs of the information technology industry. One of our main vehicles for this is IBM Skills Build, a platform where students and adult learners can have free access to online courses/badges.
IBM Skills Build is IBM’s main online platform for delivering learning to both students and adult learners who are looking to transition to another role. IBM Skills Build is the avenue to achieve IBM’s goal of skilling up 30 million people by 2030. In order to achieve this goal, IBM would need to ensure that the learning material contained in IBM Skills Build meets the needs of the information technology industry, and will help learners cross the skills gap, thereby filling the skills needs of the industry, both today and in the future (next 3 years).
In order to ensure that Skills Build continues to be the relevant to the user base, you are required to review the Skills Build content, and perform an analysis of the data provided by the UK Government Employment and Skills survey, and provide recommendations on the evolution of the IBM Skills Build, especially to determine which content should be sunset, which content is relevant, and what content IBM should consider including.
Some links to help you get started:
https://www.ibm.com/uk-en
https://skillsbuild.org/about
https://digital-skills-jobs.europa.eu/en/inspiration/resources/ibm-skillsbuild-empowering-digital-skills-all
IBM Skills Build overview:
https://bit.ly/PathWaytoLearning
UK Government Data Skills Survey (2022):
https://explore-education-statistics.service.gov.uk/find-statistics/employer-skills-survey/2022
Further research (as required) is to be carried out by the student. Requirements: 1. Familiarize with the IBM Skills Build program, how the program has evolved and what skills needs are currently addressed.
Carry out research on skills programs and their contribution to the information technology industry, business community and society at large.
2. Familiarize with IBM as an organization, and their business strategy to support the skills requirements of the fast-changing information technology industry.
3. Familiarize with the UK Government Data Skills Survey of 2022, understand the recent study skills gaps in the UK and how the skills needs have evolved.
Carry out research on any other digital skills requirements that may address future needs.
4. Analyze the data contained in the UK Government Skills Employment Survey of 2022.
Select a dataset that will support your analysis, cleanse the data as required.
5. Analyze the skills needs currently addressed by the IBM Skills Build program.
Prepare a quality dataset that will support your analysis, by using the sources given.
6. Import the data into a data analytics platform of your choice. It is recommended to use SAS Enterprise Miner, which was introduced as part of the university short course.
7. Transform the raw data by carrying out your own analysis using the software tools and produce compelling, meaningful, and relevant visualizations. Discuss your analysis in the report.
8. Frame the data set based on the requirement, apply linear regression model and interpret the results using the features of the software tool, to predict the trend of future increased skills needs. Discuss your findings in report.
The analysis must include (but not limited to):
– Projected skills shortfalls
– Sector-wise analysis
9. Reflect on the project
– what was your learning?
– challenges faced?
– what would you do differently?
10. Explain the work carried out (as separate appendices):
a. What data was collected for the analysis and what sources were used.
b. How the data was cleansed.
c. What model was selected for the predictive analysis and why.
11. Evidence of the work carried out (in report and/or as separate appendices):
a. Cleansed data sets
b. Data visualizations
c. Predictions
Requirement #5 dataset is doing an excel sheet. 6 & 7 needs someone who knows SAS miner All of the above requirements doesn’t require much words Except for the part 1,2,3,4, 9 and 10 Please show proof of answers (screen shot from the SAS and other softwares) No need for an introduction or conclusion Just answer the questions

I’m doing a final project for a statistics class, which requires graphs and othe

I’m doing a final project for a statistics class, which requires graphs and other explanations. Mastering the concepts in Introductory Statistics assists in building critical thinking skills, developing
businesses and organizations, and solving all types of problems that require data. But an understanding
of statistics extends beyond the ability to crunch numbers or use a software program. The ability to
collect, organize, and analyze data is the beginning. The ability to clearly communicate your results
to another person is the mark of true mastery.
The Assignment
In this assignment, you will choose a scenario with data – from one of 5 options provided at the end
of these directions under Project Topics – and you will construct a paper that pulls together the
statistics you have learned in order to answer a question. You will:
1. Introduce the main question, and explain the data that you will use to address it
2. Organize your data by providing appropriate charts, graphs and descriptive statistics
3. Analyze your data by conducting a hypothesis test
4. State your conclusions and recommendations
See the section Outline Of Material To Present below for a more detailed explanation of what you will
submit for each of these four sections.

Please answer all 5 questions and make sure to look at each questions that will

Please answer all 5 questions and make sure to look at each questions that will has sub-text which means; Question 1 has 1a and 1b. There is no need for paper format but just simply answering the questions. The course is actually called Quantitative Analysis For Business which is a simple statistics course. I need it in 4 hours max.

Please look over the uploaded draft. I need statistical data on the incivility a

Please look over the uploaded draft. I need statistical data on the incivility and violence within urban and suburban school districts. Which districts have discipline plans and are they successful?

Download the attached gss. Download gss.sa Download sav dataset. Open it using S

Download the attached gss. Download gss.sa Download sav dataset. Open it using SPSS and complete the following:
Make a bar chart showing the distribution of respondents’ astrological sign (variable: zodiac). Interpret the chart (make at least one comment that tells the overall story of the chart) Calculate the mean, standard deviation, and median of respondents’ Hours on the WWW per week for Internet users (variable: webhrs). Please make sure that you interpret them. Without interpretation, you will not get receive full credits even if your numbers are correct (hint: when to report median instead of mean). Calculate the 95% percent confidence interval for respondents’ Hours on the WWW per week for Internet users (variable: webhrs). Make sure your results are reported in the proper style like APA.

How can statistical analysis in mathematics provide valuable insights into patte

How can statistical analysis in mathematics provide valuable insights into patterns and trends within quantitative data?

Initial Discussion posts are due Wednesday. All interaction and corrections shou

Initial Discussion posts are due Wednesday. All interaction and corrections should be completed by Sunday. There is no interaction with peers. The responses are only visible to each individual student and the instructor. Initial posts should be thorough, completing all tasks given in the discussion prompt. All posts should demonstrate college level writing skills.
In our lessons this week, we discuss the use of crosstabulations (crosstabs) as a preliminary analysis to begin investigating the relationship between the IV and DV. A crosstab creates a “snapshot” of our data. Measures of association help to identify the strength and direction of the potential relationship.
You are now going to create and post a crosstab of your variables and a measures of association table.
Complete the following steps:
Post a brief explanation of your topic. Include your research question and a broad research hypothesis — that is, the relationship of IV to DV. (For example, educational attainment affects family income in US adults.)
Run a crosstab on your variables. Be sure to explain your findings, including a descriiption of the table, a calculation of the epsilons, and a discussion of the 10% rule.
Run the correct measure of association for your variables (Choose one – either Pearson R, Gamma, Phi, Cramer’s V or Lambda). Explain what the output means in terms of strength and direction of the relationship. Interpret Proportional Reduction of Error (PRE) using the following statement: Knowing the IV will reduce error in predicting the DV by *%.
Copy the crosstab and measure of association table into the discussion window or into a document (PDF, MS Word) and attach to discussion. If your table does not fit to the page, choose “copy special” and then “images” or take a screen shot of the table to copy/past into the window.
Special note:
When a variable is continuous (interval/ratio level of measurement), for example age of respondent, we do not run crosstabs directly because it will result in a really spread-out table with lots of zeros and low frequency cells. Such a crosstab does not help us understand the data. The correct way is to reduce the level of measurement to either ordinal level or nominal level (group the numbers into categories) by recoding and then run the crosstab. (Please refer to the Lesson Recoding in SPSS for further information.)
As a reminder, here are the guidelines for choosing your measure of association:
Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)
Both DV and IV are nominal variables and it is a 2X2 table: Phi
Both DV and IV are ordinal variables: Gamma
One variable ordinal or interval/ratio AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma
One variable ordinal or interval/ratio AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer’s V.
Both DV and IV are I/R variables: Pearson’s r

Initial Discussion posts are due Wednesday. All interaction and corrections shou

Initial Discussion posts are due Wednesday. All interaction and corrections should be completed by Sunday. There is no interaction with peers. The responses are only visible to each individual student and the instructor. Initial posts should be thorough, completing all tasks given in the discussion prompt. All posts should demonstrate college level writing skills. In our lessons this week, we discuss the use of crosstabulations (crosstabs) as a preliminary analysis to begin investigating the relationship between the IV and DV. A crosstab creates a “snapshot” of our data. Measures of association help to identify the strength and direction of the potential relationship.
You are now going to create and post a crosstab of your variables and a measures of association table. Complete the following steps:
Post a brief explanation of your topic. Include your research question and a broad research hypothesis — that is, the relationship of IV to DV. (For example, educational attainment affects family income in US adults.)
Run a crosstab on your variables. Be sure to explain your findings, including a descriiption of the table, a calculation of the epsilons, and a discussion of the 10% rule.
Run the correct measure of association for your variables (Choose one – either Pearson R, Gamma, Phi, Cramer’s V or Lambda). Explain what the output means in terms of strength and direction of the relationship. Interpret Proportional Reduction of Error (PRE) using the following statement: Knowing the IV will reduce error in predicting the DV by *%. Copy the crosstab and measure of association table into the discussion window or into a document (PDF, MS Word) and attach to discussion. If your table does not fit to the page, choose “copy special” and then “images” or take a screen shot of the table to copy/past into the window.
Special note:
When a variable is continuous (interval/ratio level of measurement), for example age of respondent, we do not run crosstabs directly because it will result in a really spread-out table with lots of zeros and low frequency cells. Such a crosstab does not help us understand the data. The correct way is to reduce the level of measurement to either ordinal level or nominal level (group the numbers into categories) by recoding and then run the crosstab. (Please refer to the Lesson Recoding in SPSS for further information.)
As a reminder, here are the guidelines for choosing your measure of association:
Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)
Both DV and IV are nominal variables and it is a 2X2 table: Phi
Both DV and IV are ordinal variables: Gamma
One variable ordinal or interval/ratio AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma
One variable ordinal or interval/ratio AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer’s V.
Both DV and IV are I/R variables: Pearson’s r

Secondary analysis of existing data collected by other researchers, for other pu

Secondary analysis of existing data collected by other researchers, for other purposes, offers researchers the potential to answer research questions without having to go through the process of collecting the data themselves. Based on your Unit III Assignment, address the prompts below.
Identify a specific academic, governmental, or commercial source of quantitative secondary data that could be used to solve the problem you stated in Part 2 of the Unit III assignment. Provide reference information for this source.
Describe how you will obtain access to the raw data.
Explain why the data are suitable for addressing your research problem.
List the limitations of using the data.
This journal should be at least two pages in length, not counting the required references page. Please thoroughly address all areas listed above, and include at least two credible sources. An abstract is not required. Please use APA compliant headings and sub-headings that align with the individual assignment requirements. Adhere to APA Style, including in-text citations and references for all sources that are used.

1. The term paper (PDF) and Python Code (.py or .ipynb) Subject: Term Paper Stat

1. The term paper (PDF) and Python Code (.py or .ipynb) Subject: Term Paper Statistical Programming 2. The paper should include the replicable and self-explanatory code and a readable documentation of your work. The documentation answers the (statistical) question in the exercise, explains the code and sums up your results in text form. Please provide concise and well thought-out answers and explanations. You can use in-line comments to explain what you do in a specific block of code. 3. Use Quarto and Jupyter 4. ChatGPT is not allowed
Only Section 5: Credit Score Classification with Gradient Boosting