## Examining multivariate techniques

Deliverable Length:   1-2 pages

Using the information from Units 1, 2, and 3, Big D Incorporated will be examining how multivariate techniques can serve the organization best and how they can be applied to its new client, the outdoor sporting goods customer. The Board of Directors has asked you to research and explain 3 major ways in which multivariate statistics are utilized in this scenario. In this case, be sure to justify your decision.

Research using the library and the Internet to find an example of how a real company has used each of the following multivariate techniques:

This can be considered a benchmark if you can justify how it could benefit Big D Incorporated.

Write a summary to upper management explaining the following:

• How can each multivariate technique be utilized in Big D Incorporated, and what purpose would each serve?
• Which technique is your preferred method, and how is your chosen multivariate technique different from the other two techniques?
• What will the Board of Directors learn from your selected technique and more importantly, how will it contribute to the overall decision-making process? Ensure that your explanation is clear and concise.

# Create a frequency table in SPSS

Topic is Gender Inequality

https://gssdataexplorer.norc.org/

http://gss.norc.org

250 words

Now that you have imported GSS 2016 dataset into your SPSS and have learned how to use GSS data explorer to find out GSS variable information, you are going to create and post a frequency table of your variables.  Complete the following steps:

Give your forum title a unique label specific to your study/variables.  Post a brief explanation of your topic which includes a bit of information about your variables: level of measurement, answer categories (yes/no, strongly agree, disagree, etc.), as well as the survey question used to collect data for this particular variable (refer to Forum 1 discussion). Include a frequency table for each of your variables. If you have one DV and one IV, you need to run frequency table for BOTH of your variables. If you have one DV and 2 IVs, you need to run three frequency tables. When you are done, explain your outputs in no more than 5 sentences for each variable. Cite numbers in the outputs to support your conclusion. When you cite %, use the % reported in “valid percent” column. This column deletes all missing values, thus is “clean.”

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To create a frequency table in SPSS

1.       Open SPSS and open your GSS data file

2.       Click Analyze

3.       Click Descriptive Statistics

4.       Click Frequencies

5.       click open Statistics

6.       Make sure that mean, median, mode, standards deviation, and variance are chosen and click “Continue”

7.      ​Choose the variable that you want to make a frequency table of and click the arrow (this will move it into the right ‘Variable’ box)

8.       Click OK

Task II. Describe the measures of central tendency (mean, median, mode) and dispersion (variance, standard deviation) for each of your variables.

Based on what you have learned in the readings and lessons this week, identify the measures for each variable and explain what they tell us. Keep in mind that the mean is more meaningful for interval/ratio variables, the median or mode for ordinal variables, and the mode for nominal variables. What do these measures summarize for us about the variable’s data?

Task III. Create charts (bar chart, pie chart, or histogram depending on your variables’ level of measurement)

Presenting your data in graphic form is also important when conducting quantitative research. Based on what you have learned from the reading and the weekly lesson, create a graphic representation of your data. Your choice of graphing tool is purely based on a variable’s level of measurement. When you are done, explain your outputs in no more than 5 sentences for each variable. It is OK if your explanation is similar to the frequency table interpretation, since chart is a different data presentation on the SAME variable. Cite numbers in the outputs to support your conclusion.

Basic rules:

Nominal: bar chart or pie chart

Ordinal: bar chart or pie chart

Interval/Ratio: histogram or line chart

To Create a Chart

2.       Click Charts

3.       Click choice of format (depending on your variable’s level of measurement)

4.       Click OK

5.       Continue with steps 5-6

Copy all of the frequency tables and charts by copy and pasting them into a document (PDF, MS Word) and attach to forum discussion. If your table/chart does not fit to the page, choose “copy special” and then “images.” Paste images to the word document and the problem will be solved.

If you need further guidance, refer to the step-by-step screenshots attached at the end of the rubrics.

## Assignment 2

1)  Read attached case study. Your assignment must be two to three pages in length APA style (excluding title and reference pages). Utilize your reference listed below and at least one additional scholarly source.  Based on the information in this case, thoroughly answer the following questions below:

· Write a mission statement that reflects this new direction for St. Mary’s.

· Write a vision statement reflecting the new mission statement.

· What type of strategy did the leadership team at St. Mary’s pursue?

· Which organizations in the community might view the wellness center as a new form of competition?

· What factors described in this chapter might affect the implementation of this new strategy?

Baack, D. E. & Fischer, A. (2013). The essentials of managing in the healthcare industry [Electronic version]. Retrieved from https://content.ashford.edu/

DUE 8/16/19 9AM EASTERN W/TURNITIN REPORT

# Forecasting impacts to an organization

Unit 2: Discussion

Introduction

Forecasting impacts to an organization. As production manager last unit in the Kibby and Strand simulation you gained insights into how raw materials were turned into finished goods. This unit you will learn more about the front end of the operational process employed by the company. Specifically, you will learn how to manage suppliers who provide the raw materials used in the production of the company’s textile products. Some challenges you will face are: 1) which suppliers provide the best quality raw materials; 2) which suppliers are the most reliable; and 3) which suppliers have the most competitive prices.

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The simulation scenario will pose many opportunities for decision making and forecasting, and if you make a poor decision regarding suppliers it will impact the ability of Kibby and Strand to meet its contractual obligations, leading to dissatisfied customers. Since customer satisfaction weighs heavily on future contracts, you can’t simply make the best decision for the moment, but rather the best decision for the long haul. This scenario provides a realistic illustration of the issues textile companies face across the U.S. It’s extremely important that operations professionals have an above average comfortable level when it comes to establishing grounded assumptions and conducting and interpreting financial and operational forecasts. In its simplest form, forecasting is a process that represents an “educated guess”. In business, we use time series methods, the indicator approach, or regression analyses to forecast the nature of a situation or future values. The data we observe when forecasting fall into one of four types: trended patterns, seasonal patterns, cyclical patterns, or irregular patterns (Kros & Brown, 2013). Forecasting models are used to predict consumer demand, which, in turn, aids management in forecasting staffing requirements. In addition, to demand forecasts, management routinely engages in financial forecasting, which includes, but is not limited to: sales growth, economic predictions, and forecast future cash flows. In order to perform forecasts, it’s important that the management team signoff on the underlying assumptions used to complete these analyses, such as population growth and technology development. The following represents the typical steps one undertakes when preparing for and conducting a forecast (Investopedia, n.d.):

1. A problem or data point is chosen. This can be something like “will people buy a high-end coffee maker?” or “what will our sales be in March next year?”

2. Theoretical variables and an ideal data set are chosen. This is where the forecaster identifies the relevant variables that need to be considered and decides how to collect the data.

3. Assumption time. To cut down the time and data needed to make a forecast, the forecaster makes some explicit assumptions to simplify the process.

4. A model is chosen. The forecaster picks the model that fits the data set, selected variables and assumptions.

5. Analysis. Using the model, the data is analyzed and a forecast made from the analysis.

6. Verification. The forecaster compares the forecast to what actually happens to tweak the process, identify problems or in the rare case of an absolutely accurate forecast, pat himself on the back.

Sources:

Kros, J. F., & Brown, E. (2013). Health Care Operations and Supply Chain Management.  San Francisco, CA: John Wiley & Sons.

Unit Learning Outcomes

1. Develop a plan for forecasting impacts to an organization’s bottom line. (CLO 1, 2, 4, and 7)

2. Demonstrate how to perform forecasting using data and statistics. (CLO 4 and 5)

3. Identify trends and patterns in data as they apply to forecasting. (CLO 1, 3, 5, and 7)

4. Develop a data collection plan that will permit the creation of an accurate and reliable forecasting model. (CLO 3, 4, and 5)

Directions

Accessing McGraw-Hill Connect

Follow these steps to view the scenario.

Initial Posting

Go to McGraw-Hill Practice Operations to view the scenario.