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Question One
From the bibliography of your proposed dissertation study, select a peer-reviewed journal article that was done with a quantitative methodology. Cite the article and summarize the study in one paragraph. Then categorize it according to each of the following dimensions:
- Experimental, quasi-experimental, or non-experimental
- Descriptive, predictive, or explanatory
- Retrospective, cross-sectional, or longitudinal
Why did you categorize the article as you did? Do articles in your field of interest commonly fall into this category? Why or why not?
Question Two
What are the primary factors that make it more challenging to conduct experimental studies in the field of education or leadership? Why are these significant? How do these factors affect your own research design for the dissertation study?
MODULE 2
Module 2 Problem Set
EXAMPLE
Grand Canyon University: RES-866
Approaches to Research Design and Data Analysis
May 15, 2019
Running head: ASSIGNMENT TITLE HERE
1
Running head: MODULE 2
Introduction
Understanding and interpreting data is a vital component to a learner’s research as it reflects the study results. Properly analyzing the data is also crucial as this portrays the outcomes and delivers research findings which is the purpose of completing the study initially. Once data is extracted and analyzed, further development of the topic is discussed and shared allowing for a deeper sense of knowledge of the included variable, perceptions, and anything discovered throughout the study. Astroth and Chung (2018) discussed the importance of reviewing quantitative research studies highlighting the importance of ensuring the results are presenting and interpreted correctly. This article is geared towards nurses as they utilize evidence-based practices throughout many health care settings therefore properly analyzing data and accurately reporting results is critical in the potential care provided. For the purpose of this paper, the learner completed the assigned tasks of Module 2 Problem set which is provided below.
Drinks | Learning Activity 2.11
1. Create standardized scores for all scale variables (price through alcohol).
[DataSet1] \\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Price per 6-pack
35
1.59
7.19
3.0274
1.12343
Cost per 12 Fluid Ounces
35
.27
1.20
.5057
.18732
Calories per 12 Fluid Ounces
35
68
175
139.77
24.447
Sodium per 12 Fluid Ounces in mg
35
6
27
14.66
6.145
Alcohol by Volume (in %)
35
2.30
5.50
4.5771
.60298
Valid N (listwise)
35
a. Which beverages have positive standardized scores on every variable?
· The beverages including each variable with positive standardized scores includes UA, UH, UL, UR, and SA.
b. What does this mean?
· Based on the raw data, these beverages are at or above the mean average or group mean
2. (a) What is the most extreme z-score on each variable? (b) What is the most extreme z-score across all variables?
a.
Variable
Product
Z-Score
price
SA
3.70524
cost
SA
3.70636
calories
UNR
-2.93581
sodium
PF & PJ
2.00859
alcohol
UNR
-3.77651
b.
cost
SA
3.70636
3. What beverage is most typical of all beverages, that is, has z-score values closest to 0 for these variables?
a. The most common beverage is UIR having the closest z-score value to 0.
4. (a) If the variable is normally distributed, what percentage of cases should be above 1 standard deviation from the mean or below 1 standard deviation from the mean?
a. 68%
(b) Calculate this percentage for a couple of the variables. Is the percentage of beverages with an absolute z-score above 1 close to the theoretical value?
b. Upon running calculations for some of the variables, the percentages were above 1 with an absolute z-score and close to the theoretical value.
Notes
Output Created
14-MAY-2019 17:05:54
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav
Active Dataset
DataSet1
File Label
SPSS/PC+
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
35
Missing Value Handling
Definition of Missing
User defined missing values are treated as missing.
Cases Used
All non-missing data are used.
Syntax
DESCRIPTIVES VARIABLES=price cost calories sodium alcohol
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.25
Variables Created or Modified
ZzZz01
Zscore(price) Price per 6-pack
ZzZz02
Zscore(cost) Cost per 12 Fluid Ounces
ZzZz03
Zscore(calories) Calories per 12 Fluid Ounces
ZzZz04
Zscore(sodium) Sodium per 12 Fluid Ounces in mg
ZzZz05
Zscore(alcohol) Alcohol by Volume (in %)
Census | Learning Activity 3.9
1. Run the Frequencies procedure on the following variables: sex, wrkstat (Labor Force Status), paeduc (Father’s highest degree), and satjob (Job or Housework).
a. What is the scale of measurement for each?
· Sex – nominal
· Work stat – nominal
· Sat job – nominal
· Par educ – scale
b. Request appropriate summary statistics and charts.
Statistics
RESPONDENTS SEX
LABOR FRCE STATUS
FATHERS HIGHEST DEGREE
JOB OR HOUSEWORK
N
Valid
2023
2021
1553
1536
Missing
0
2
470
487
Median
2.00
2.00
1.00
1.00
Mode
2
1
1
1
RESPONDENTS SEX
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
MALE
929
45.9
45.9
45.9
FEMALE
1094
54.1
54.1
100.0
Total
2023
100.0
100.0
LABOR FRCE STATUS
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
WORKING FULLTIME
1003
49.6
49.6
49.6
WORKING PARTTIME
211
10.4
10.4
60.1
TEMP NOT WORKING
53
2.6
2.6
62.7
UNEMPL, LAID OFF
74
3.7
3.7
66.4
RETIRED
336
16.6
16.6
83.0
SCHOOL
57
2.8
2.8
85.8
KEEPING HOUSE
227
11.2
11.2
97.0
OTHER
60
3.0
3.0
100.0
Total
2021
99.9
100.0
Missing
NA
2
.1
Total
2023
100.0
FATHERS HIGHEST DEGREE
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
LT HIGH SCHOOL
538
26.6
34.6
34.6
HIGH SCHOOL
679
33.6
43.7
78.4
JUNIOR COLLEGE
38
1.9
2.4
80.8
BACHELOR
187
9.2
12.0
92.9
GRADUATE
111
5.5
7.1
100.0
Total
1553
76.8
100.0
Missing
IAP
354
17.5
DK
109
5.4
NA
7
.3
Total
470
23.2
Total
2023
100.0
JOB OR HOUSEWORK
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
VERY SATISFIED
778
38.5
50.7
50.7
MOD. SATISFIED
570
28.2
37.1
87.8
A LITTLE DISSAT
135
6.7
8.8
96.5
VERY DISSATISFIED
53
2.6
3.5
100.0
Total
1536
75.9
100.0
Missing
IAP
453
22.4
DK
19
.9
NA
15
.7
Total
487
24.1
Total
2023
100.0
Bar Chart
2. (a) For which of these variables is it appropriate to use the median? (b) What conclusions can you draw about the distributions of these variables?
a. The variables for which it is most appropriate to use the median are high school education (paeduc) and Job or Housework (satjob) as these measurements are best for this category.
b. The conclusions that can be drawn include that with more education, the higher propensity of having full time employment. More than half reported being satisfied with their employment and more than half did not attend college.
3. (a)What percent of respondents have a bachelor’s degree, or higher? (b)What percent of respondents are working?
a. 14.7% of respondents have a bachelor’s degree or higher
b. 60% of respondents are working either full time or part time
4. How might you combine some of the categories of wrkstat to ensure that there are a sufficient number of respondents in each category?
a. Completing a summary analysis could lend support in determining grouping availability however some of categories that could ensure a sufficient amount of respondents could be employed, retired, and keeping house as they represent cross-categories with high percentages to fulfill the gap.
FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
Frequencies
Notes
Output Created
14-MAY-2019 16:59:13
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Census.sav
Active Dataset
DataSet2
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
2023
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Syntax
FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
Resources
Processor Time
00:00:02.06
Elapsed Time
00:00:01.31
Drinks | Learning Activity 4.18
1. Run Frequencies on the variable alcohol, requesting the summary statistics median and mean, plus a histogram with a superimposed normal curve. Suppress the display of the frequency table.
Statistics
Alcohol by Volume (in %)
N
Valid
35
Missing
0
Mean
4.5771
Median
4.7000
2. (a) What is the value of value of alcohol that splits the distribution in half? (b) Is the median the same as the mean? (c) Which value is lower? (d) What does that tell you about the shape of the distribution of alcohol?
a. 4.7 splits the distribution in half
b. The mean and median are not the same as the mean is 4.5771 and the median is 4.7
c. The mean of 4.5771 is lower than the median of 4.7
d. The data is skewed negatively which is indicated by the longer tail
3. (a) Does the histogram verify your description of the distribution of alcohol? (b) How does it differ from a normal distribution?
a. Yes, as it does support being it shows a negative distribution on the left versus a positive distribution on the right which presents alignment
b. Normal distribution is centered and symmetrical which is not apparent as it is skewed left presenting a negative distribution.
4. Run Descriptives to obtain default statistics for price and calories. (a) On which variable is there more dispersion? (b) Is it even realistic to compare these two variables since they are on different scales?
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Price per 6-pack
35
1.59
7.19
3.0274
1.12343
Calories per 12 Fluid Ounces
35
68
175
139.77
24.447
Valid N (listwise)
35
a. There is more dispersion with Calories per 12 Fluid Ounces
b. It is not logical to compare these variables being they are on different scales
5. Continuing your analysis of price and calories, run the Explore procedure for these two variables. Request a histogram in addition to the defaults.
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Price per 6-pack
35
100.0%
0
0.0%
35
100.0%
Calories per 12 Fluid Ounces
35
100.0%
0
0.0%
35
100.0%
Price per 6-pack
Calories per 12 Fluid Ounces
Calories per 12 Fluid Ounces
1. Does the standard error of each variable help you better determine which variable has more dispersion?
a. There is a lack of accuracy therefore it does not better identify which has more dispersion
2. Review the boxplots and histogram for each variable. (a) Which one has more outliers? (b) What are the outliers on each? (c) Which variable now appears to have more dispersion, based on these graphs? (d) Does that match what you expected based on the statistics?
a. Calories per 12 Fluid Ounces is the variable with the highest outliers
b. The outliers are 2 and 6 for Calories per 12 Fluid Ounces
c. The most dispersion is Price per pack after the outliers are removed
d. Yes, this does match my expectations
Price per 6-pack Stem-and-Leaf Plot
Frequency Stem & Leaf
4.00 1 . 5677
6.00 2 . 122344
15.00 2 . 555555666777899
2.00 3 . 13
1.00 3 . 6
2.00 4 . 23
5.00 Extremes (>=4.6)
Stem width: 1.00
Each leaf: 1 case(s)
Calories per 12 Fluid Ounces Stem-and-Leaf Plot
Frequency Stem & Leaf
6.00 Extremes (=<113)
.00 13 .
2.00 13 . 56
6.00 14 . 044444
9.00 14 . 555779999
7.00 15 . 0122344
2.00 15 . 57
1.00 16 . 2
2.00 Extremes (>=170)
Stem width: 10
Each leaf: 1 case(s)
FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
Frequencies
Notes
Output Created
14-MAY-2019 16:59:13
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Census.sav
Active Dataset
DataSet2
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
2023
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Syntax
FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.
Resources
Processor Time
00:00:02.06
Elapsed Time
00:00:01.31
Frequencies
Notes
Output Created
14-MAY-2019 17:11:58
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav
Active Dataset
DataSet1
File Label
SPSS/PC+
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
35
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Syntax
FREQUENCIES VARIABLES=alcohol
/STATISTICS=MEAN MEDIAN
/HISTOGRAM NORMAL
/FORMAT=LIMIT(10)
/ORDER=ANALYSIS.
Resources
Processor Time
00:00:00.28
Elapsed Time
00:00:00.33
Descriptives
Notes
Output Created
14-MAY-2019 17:13:38
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav
Active Dataset
DataSet1
File Label
SPSS/PC+
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
35
Missing Value Handling
Definition of Missing
User defined missing values are treated as missing.
Cases Used
All non-missing data are used.
Syntax
DESCRIPTIVES VARIABLES=price calories
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.
Resources
Processor Time
00:00:00.02
Elapsed Time
00:00:00.27
Variables Created or Modified
ZqZq01
Zscore(price) Price per 6-pack
ZqZq02
Zscore(calories) Calories per 12 Fluid Ounces
Explore
Notes
Output Created
14-MAY-2019 17:16:56
Comments
Input
Data
\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav
Active Dataset
DataSet1
File Label
SPSS/PC+
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
35
Missing Value Handling
Definition of Missing
User-defined missing values for dependent variables are treated as missing.
Cases Used
Statistics are based on cases with no missing values for any dependent variable or factor used.
Syntax
EXAMINE VARIABLES=price calories
/PLOT BOXPLOT STEMLEAF HISTOGRAM
/COMPARE GROUPS
/STATISTICS DESCRIPTIVES
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.
Resources
Processor Time
00:00:00.88
Elapsed Time
00:00:00.86
Conclusion
This module has provided an opportunity for the learner to display proper use of SPSS, data manipulation, and data analysis over a course of exercises. There was much to be explored in properly understanding and interpreting the information. In following the steps to produce the guided results, the opportunity to produce charts and validate data was included. As shared, the ability to produce valid data is only a portion of the purpose research as being able to understand and provide generalization is just as important which has been portrayed. The continued analysis of the problem sets provided a solid foundation for upcoming doctoral research.
References
American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: Author.
Astroth, K. S., & Chung, S. Y. (2018). Focusing on the Fundamentals: Reading Quantitative Research with a Critical Eye. Nephrology Nursing Journal, 45(3), 283. Retrieved from https://search-ebscohost-com.lopes.idm.oclc.org/login.aspx?direct=true&db=edswss&AN=000437552000008&site=eds-live&scope=site
SPSS (2010) Introduction to statistical analysis using IBM SPSS Statistics student guide retrieved form: RES866.7P5CL_introduction_to_statistical_analysis_using_ibm_spss_statistics.pdf
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