Statistics

COMPETENCY ASSESSMENT Introduction Assessment Rubric and Minimum Submission Requirements

This competency assessment assesses the following Outcome(s):

MM207M3: Determine the relationship between two variables.

GEL-1.02: Demonstrate college-level communication through the composition of original materials in Standard English.

It is time to demonstrate what you have learned in this module! One of the concepts we covered in this module was the interpretation and calculation of the relationship between any two variables. You will be required to calculate correlation coefficients. You will also be required to interpret and compare relationships between pairs of variables using the associated correlation coefficients. You will be required to create scatter plots and interpret scatter plots, such as whether the two variables in the scatter plot are related, the apparent strength of the relationship, and whether the direction of the relationship is positive or negative. The assessment will also cover linear regression. You will have to use regression equations for prediction and will have to understand and interpret such equations. Throughout this module and on assessments, you are welcome to use Excel as you wish.

You will be completing the Competency Assessment in MyLab. You will be applying concepts from logic to answer the questions about a variety of real life applications and situations.

Please note the following when completing the Competency Assessment:

The Competency Assessment must be completed in one sitting. You do not have the option to save and come back to finish the assessment. You have unlimited attempts to successfully complete the Competency Assessment. The Competency Assessment will be manually scored by your instructor. Within the Competency Assessment you will NOT find support resources, such as solved examples that were available in the MyLab These support resources are not available in the Readiness or Competency Assessments.

Part 2 Excel is an excellent and powerful tool that can be used to investigate correlation and regression. For this assignment, complete the following.

1. Choose any Excel dataset from Content > Course Resources. Include the name of the dataset. From that dataset, select any two quantitative variables that you suspect will be related (such as age and height for example). What is the name of the dataset you have chosen? Which two variables did you choose?

2. Next, using Excel, calculate the correlation coefficient (r value) between the two variables. Recall that the Excel “formula” for correlation is “=CORREL”. What is the r value for the two variables that you have chosen? Is it positive or negative? Is it strong, medium, or weak? Note that it is best to have an r value that is medium or strong. It is recommended that you try a few different variables until you find two variables with an r value between .5 and 1 (or between -.5 and -1).

3. Next, use Excel to create a scatterplot for the two variables. You decide which variable will be dependent (y) and which will be independent (x). On the scatterplot, include the “trendline” and the “equation for the line” using Excel options. Attach your scatterplot to your post.

4. Finally, using the equation of the line that you generated above, substitute any reasonable value for x (your chosen independent variable) and solve the equation for y (your chosen dependent variable). It is up to you to determine which of your two variables is x and which is y. What prediction do you get? Show all of your work. In other words, type out the equation, substitute a value for x, and show your solution for y.

5. Write 2 - 3 paragraphs that describe what your equation represents. Discuss which variable is the independent variable and which is the dependent variable. Why do you think the dependent variable might “depend” on the independent variable? Explain how your equation can be used to estimate values for the dependent variable. Finally, explain the difference between correlation and cause. Give an example of two variables that are related, but are not causal. Your paragraphs should follow the conventions of Standard English (correct grammar, punctuation, and spelling). Your writing should be well ordered, logical and unified, as well as original and insightful. In addition to fulfilling the specifics of the Assignment, APA citation style* should be followed.

https://purdueglobal.brightspace.com/d2l/le/content/303708/viewContent/17838447/View 7/23/24, 10:18 AM Page 1 of 2

You can find numerous APA resources in the Writing Center Writing Reference Library on the Research, Citation, and Plagiarism page .

Submitting Your Assessment Part 2: When you are ready to submit your Course Assessment Part 2, click on the Course Assessment Dropbox.

https://purdueglobal.brightspace.com/d2l/le/content/303708/viewContent/17838447/View 7/23/24, 10:18 AM Page 2 of 2

Sheet1

AGE IN MONTHS	ID Tag #	SEX (1 is Male and 2 is Female)	HEAD LENGTH (inches)	HEAD WIDTH (inches)	BODY TEMP (F)	BODY LENGTH (inches)	WEIGHT	MONTH TAGGED
19	5687	1	11	5.5	99	53	80	October
55	3732	1	16.5	9	91	67.5	344	December
81	4599	1	15.5	8	91	72	416	August
115	6783	1	17	10	97	72	348	October
104	2104	2	15.5	6.5	98	62	166	November
100	2766	2	13	7	97	70	220	December
56	9114	1	15	7.5	92	73.5	262	August
51	4243	1	13.5	8	94	68.5	360	October
57	1847	2	13.5	7	92	64	204	October
53	8142	2	12.5	6	99	58	144	January
68	5602	1	16	9	98	73	332	November
8	2177	1	9	4.5	91	37	34	December
44	2672	2	12.5	4.5	93	63	140	December
32	1150	1	14	5	91	67	180	October
20	5954	2	11.5	5	94	52	105	August
32	9123	1	13	8	89	59	166	December
45	2781	1	13.5	7	93	64	204	October
9	5551	2	9	4.5	93	36	26	January
21	2058	1	13	6	90	59	120	January
177	3852	1	16	9.5	99	72	436	December
57	8456	2	12.5	5	89	57.5	125	March
81	3596	2	13	5	97	61	132	February
21	4844	1	13	5	98	54	90	January
9	1458	1	10	4	98	40	40	December
45	9114	1	16	6	99	63	220	November
9	4998	1	10	4	96	43	46	November
33	9109	1	13.5	6	98	66.5	154	October
57	6451	2	13	5.5	91	60.5	116	August
45	3162	2	13	6.5	95	60	182	October
21	7209	1	14.5	5.5	89	61	150	August
10	3027	1	9.5	4.5	95	40	65	December
82	4372	2	13.5	6.5	89	64	356	August
70	5468	2	14.5	6.5	95	65	316	March
10	2212	1	11	5	96	49	94	February
10	3152	1	11.5	5	92	47	86	February
34	9397	1	13	7	96	59	150	January
34	5253	1	16.5	6.5	95	72	270	October
34	5108	1	14	5.5	97	65	202	March
58	6737	2	13.5	6.5	90	63	202	April
58	4772	1	15.5	7	93	70.5	365	December
11	5779	1	11.5	6	94	48	79	December
23	9710	1	12	6.5	89	50	148	November
70	592	1	15.5	7	89	76.5	446	January
11	8036	2	9	5	93	46	62	October
83	1243	2	14.5	7	95	61.5	236	August
35	6133	1	13.5	8.5	89	63.5	212	May
16	6959	1	10	4	95	48	60	June
16	8835	1	10	5	97	41	64	February
17	8954	1	11.5	5	93	53	114	December
17	6318	2	11.5	5	95	52.5	76	October
17	8709	2	11	4.5	91	46	48	November
8	4177	2	10	4.5	98	43.5	29	October
83	2701	1	15.5	8	98	75	514	October
18	4025	1	12.5	8.5	97	57.3	140	February