Provide (2) 200 words response with a minimum of 1 APA references for RESPONSES 1 AND 2 below. Responses may include direct questions. In your peer posts, compare the probabilities that you found with those of your classmates. Were they higher/lower and why? In your responses, refer to the specific data from your classmates’ posts. Make sure you include your data set in your initial post as well. Attached are the excel docs for both responses.
RESPONSE 1:
For this weeks forum I determined that my average price for the SUV’s that I selected was $49,903.60. Out of the 10 vehicles that I chose 6 of the cars were less than the average of all the cars price giving me a probability of p=.60 and a q=.40. When I calculated the probability of 10 randomly selected cars that exactly 4 of them will fall below my average I got 11%. When I calculated the probability that fewer than 5 of them would fall below the average I got slightly over 16%. Next, I calculated the probability that more than 6 of them would fall below my average and got 38%. What was interesting is that when I calculated the probability that at least 4 cars would fall below the average of my vehicles I got 94.5%. I think that this is a good exercise to learn in being able to speak to the likelihood that a car dealer will likely have the vehicle a customer is looking for based on the customer’s price point. If the dealer knows their averages they can also make suggestions and marketing assumptions that they have a good probability that a customer will find a vehicle of their choice within their price range using the information we covered in this weeks lesson. The formulas based on the pdf were explained at the bottom of the attached spreadsheet.
RESPONSE 2:
The average of my vehicles came out to $16,593. Half of the car’s prices fell below the average which made my probability success and failure 0.5. Both p=0.5 and q=0.5.
Average = $16,593
5 of my vehicles fall below the average
P= 5/10
P or Success = 0.5
Q = 1-p
Q = 1-0.5
Q or Failure = 0.5
In another random sample using the same data, the probability that exactly 4 cars would fall below the average is 21%.
In another random sample using the same data, the probability that fewer than 5 vehicles would fall below the average is 62%.
In another random sample using the same data, the probability that more than 6 vehicles will fall below the average is 17%.
In another random sample using the same data, the probability that at least 4 vehicles will fall below the average is 83%.
The results did not particularly surprise me. Since my probability was 0.5 is made it easier to simply look at the numbers and make a guess. The result that probably surprised me the most was how little the probability for exactly 4 vehicles falling below the average was. But then again, anytime you see the word “exactly” I would imagine a lower probability. Another extremely helpful pdf for this exercise. It was easy to follow and helped me understand the material more clearly.
Jenny

Deliverable 6 – Analysis with Correlation and Regression

Competency

Determine and interpret the linear correlation coefficient, and use linear regression to find a best fit line for a scatter plot of the data and make predictions.

Scenario

According to the U.S. Geological Survey (USGS), the probability of a magnitude 6.7 or greater earthquake in the Greater Bay Area is 63%, about 2 out of 3, in the next 30 years. In April 2008, scientists and engineers released a new earthquake forecast for the State of California called the Uniform California Earthquake Rupture Forecast (UCERF).
As a junior analyst at the USGS, you are tasked to determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and depths from the earthquakes. Your deliverables will be a PowerPoint presentation you will create summarizing your findings and an excel document to show your work.
Concepts Being Studied

• Correlation and regression
• Creating scatterplots
• Constructing and interpreting a Hypothesis Test for Correlation using r as the test statistic

You are given a spreadsheet 
that contains the following information:

• Magnitude measured on the Richter scale
• Depth in km

Using the spreadsheet, you will answer the problems below in a PowerPoint presentation.

What to Submit

The PowerPoint presentation should answer and explain the following questions based on the spreadsheet provided above.

• Slide 1: Title slide
• Slide 2: Introduce your scenario and data set including the variables provided.
• Slide 3: Construct a scatterplot of the two variables provided in the spreadsheet. Include a description of what you see in the scatterplot.
• Slide 4: Find the value of the linear correlation coefficient r and the critical value of r using α = 0.05. Include an explanation on how you found those values.
• Slide 5: Determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and the depths from the earthquakes. Explain.
• Slide 6: Find the regression equation. Let the predictor (x) variable be the magnitude. Identify the slope and the y-intercept within your regression equation.
• Slide 7: Is the equation a good model? Explain. What would be the best predicted depth of an earthquake with a magnitude of 2.0? Include the correct units.
• Slide 8: Conclude by recapping your ideas by summarizing the information presented in context of the scenario.

Along with your PowerPoint presentation, you should include your Excel document which shows all calculations.

Deliverable 3 – Confidence Intervals

Competency

Given a real-life application, develop a confidence interval for a population parameter and its interpretation.

Instructions

Scenario (information repeated for deliverable 01, 03, and 04)
A major client of your company is interested in the salary distributions of jobs in the state of Minnesota that range from $30,000 to $200,000 per year. As a Business Analyst, your boss asks you to research and analyze the salary distributions. You are given a spreadsheet 
that contains the following information:

• A listing of the jobs by title
• The salary (in dollars) for each job

You have previously explained some of the basic statistics to your client already, and he really liked your work. Now he wants you to analyze the confidence intervals.
Background information on the Data
The data set in the spreadsheet consists of 364 records that you will be analyzing from the Bureau of Labor Statistics. The data set contains a listing of several jobs titles with yearly salaries ranging from approximately $30,000 to $200,000 for the state of Minnesota.

What to Submit

Your boss wants you to submit the spreadsheet with the completed calculations. Your research and analysis should be present within the answers provided on the worksheet.