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Buy Research Paper OnIine _PL4001 SOCIAL RESEARCH METHODS (USING SPSS)


Buy Research Paper OnIine _PL4001 SOCIAL RESEARCH METHODS (USING SPSS)

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IPL4001 SOCIAL RESEARCH METHODS

INSTRUCTIONS FOR QUANTITATIVE ASSIGNMENT

(Updated December/January 2017)

Quantitative research exercise 1,500 words (30%)

(LO 4, 5, 9, 10)

  • Understand the processes involved in quantitative data collection and analysis
  • Critically evaluate the significance of research findings in substantive area(s)
  • Demonstrate research skills appropriate for quantitative research methods
  • Demonstrate critical evaluation skills relevant to substantive research area(s)

 

Students will be expected to write up a short research report (1,500) on data collected as part of

a class exercise exploring Students’ Attitudes to Research.

 

The exercise will include the two main components

  1. Setting up an SPSS database (this will be undertaken as part of a specific SPSS skills workshop). Please note that attendance at this workshop is strongly recommended regardless of the student’s level of skill in developing SPSS databases, as specific instructions on how to conduct descriptive statistics and ‘t-tests’ required for the report will be addressed in this workshop.

 

  1. Producing a research report (1,500 words).

 

Students will be provided with completed MA/MSc students’ attitudes to research database.

 

This will be on myUniHub under the MA Social Work folder and the MSC Mental health Studies/Dual Diagnosis/MSc Complementary Health folders.

 

You will find the data under the module IPL4001 and SPSS Workshop Materials. The name of the file is ‘January SPSS Database 2017’.

 

The data will have been collected from students taking IPL4001 (Social Work and Health Students), who have been asked to complete an ‘attitudes to research’ questionnaire. Students will be expected to:

 

OUTLINE OF BRIEF RESEARCH REPORT ; please use the following format (Headings 1 to 5 below)

 

Heading 1       –           Introduction/statement of the problem

 

Should include a short statement regarding the challenges of teaching research in undergraduate/post graduate courses and how in particular social work/nursing students are somewhat anxious about undertaking ‘quantitative research’.

 

Heading 2       –           Literature review

 

Should include a short/brief review on current knowledge regarding post graduate student’s attitudes to research in general and specifically attitudes to the use of quantitative methods.  The expectation is that students include 3-4 references on current literature addressing this issue.


Heading 3       –           Methods

 

Sub heading 1             Sample – describe what type of sampling was undertaken e.g. purposeful,

convenience etc, size of study population

 

Sub heading 2             Setting – describe where the research took place e.g. University setting, Department of Mental Health and Social Work, etc

 

Sub heading 3             Instruments – describe the instrument used, including its reliability and validity. A copy of the scale ‘The Attitudes Towards Research Scale (ATR)’  can be located at http://www.stat.auckland.ac.nz/~iase/serj/SERJ4(1)_Papanastasiou.pdf

 

Or a copy of the pdf paper has been uploaded into the folder SPSS Workshop Materials

 

Sub heading 4             Data collection/procedure– describe how the data was collected e.g. questionnaires were distributed within the class room and students were given 10-15 minutes to complete etc…

 

Sub heading 5             Data analysis – provide an overview of what analysis was employed and rationale for the use of descriptive statistics and t-tests.  Students should not just describe the analysis e.g. the mean was calculate for age, but should offer information on why the mean is calculated.

 

Heading 4                   Findings or Results (Student can choose which term to use)

 

Should include all the study findings, including where relevant the use of histograms or tables.  Please note tables and graphs are not part of the word allowance and should not be in the appendix.  Please do not ‘discuss’ your results in this section, this should be only be in the discussion.  When reporting the results please ensure that you do not present the same results in different formats e.g. in the text, then in a table, and again in graph form.  The aim is to ‘pull out the relevant data’ (usually the most important finding), report this in the text and then refer the reader to the remaining findings in the table/graph/figure.

Results should be reported as follows

Sub heading 1             % Response rate (note: the total number of students who could have taken part over the number who actually took part e.g.

This year (2016 – 17) there are 70 students registered for the module; please check how many actually took part in the study on the database file

Sub heading 2             Sample profile (including gender, age, highest education qualification attained, previous research experience, course status)

Sub heading 3             Attitude profile (include the mean scores for total research attitude and five sub scales (Life, Career, Positive, Difficulty and Anxiety for study participants)(see notes on analyses on how you might tackle the analysis and presentation of findings

Sub heading 4             Results for Hypotheses 1 and 2

 

Heading 5                   Discussion

 

You should include a discussion and interpretation of key study findings and refer back to relevant material you cited in the Literature Review (Heading 2).

NOTES ON MAKING YOUR ANALYSES

Students will be expected to produce descriptive statistics from the data provided.

 

How to analyse and profile sample

Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data.

 

Students should report on the following descriptive statistics (Heading 4 Sub heading 2)

  • Overall response rate – please note that 70 students were registered on the module and thus potentially available to participate
  • Gender – frequency/percent
  • Mean age (including Standard Deviation, min and max)
  • Highest education qualification attained – frequency/percent
  • Previous research experience – frequency/percent
  • Course status – frequency/percent

 

 How to interpret and report the findings for Attitude towards Research (Heading 4, Sub heading 3)

  • Mean score of total research attitude (including Standard Deviation, min and max)
  • Mean score of each of the five sub-scales (including Standard Deviation, min and max)

 

Total Research Attitude (new variable created) is determined by adding up the scores of each of the 32 items on the questionnaire.  Given that the scale responses are between 1 (negative attitude) and 7 (positive attitude), the minimum score a respondent could achieve on this scale is 32 (i.e. 1×32) and maximum score will be 224 (i.e. 7 x 32) (neutral point = 96).  Hence to determine the meaning of the score a respondent gets using this scale i.e. total research attitude, the higher the score the more positive the attitude.

The ‘concept’ of attitude to research is multidimensional (i.e. 5 areas that make up total attitude) and the scale measures each dimension (e.g. Life, Anxiety, Difficulty, Career, and Positive) – please refer to the full paper by ELENA C. PAPANASTASIOU the researcher who developed the instrument for a more in depth explanation of development of each dimension/factor.   A copy of this paper has been uploaded as a pdf on myUniHub or you can download it at:  http://www.stat.auckland.ac.nz/~iase/serj/SERJ4(1)_Papanastasiou.pdf

It therefore is important to appreciate how the ‘total research attitude’ is reflected and to draw further meaning/understanding by exploring each dimension in its own right.  Hence each domain minimum and maximum scores need to be known so that the respondents score can be interpreted as positive or negative.  The following table below shows the range of possible minimum score (negative attitude) and maximum score (positive attitude) for each domain. (In practice, remember that this cohort’s actual results may not go as low as the minimum or as high as the maximum score for each item).

Life (4 items) (min score 4 max score 28) (neutral point 12)

Anxiety (8 items) (min score 8 max score 56) (neutral point 24)

Difficulty (3 items) (min score 3 max score 21) (neutral point 9)

Career (9 items) (min score 9 max score 63) (neutral point 27)

Positive (8 items) (min score 8 max score 56) (neutral point 24)

Reporting the findings in your research report

For the purposes of the research report, you are expected to report and interpret the mean score for overall research attitude for the entire group, and the mean score for each domain.

 

You have two options of determining how best to interpret the means of the overall attitude score and each of the subscales (domains).  You can work out the mean of the means by dividing the mean for each total subscale score by the number of items in each sub scales, this will give you a ‘mean of the means’ which will be somewhere between 1 and 7 ( the original range of scores that participants could give on the Likert scale).  If we accept that 4 is neutral i.e. neither positive or negative then you can interpret the scores against this.

 

The second way would be to subtract the mean score for each subscale from the median score for each subscale and determine whether the study participants scores are plus/minus – if plus i.e. higher than the median then you can interpret that this subscale is going in the direction of being positive and vice versa, you can also interpret which subscale appears to score the highest positive score.

 

 

How to analyse and interpret the Hypotheses (Heading 4, Sub heading 4)

 

In addition to undertaking the above, students will expected to address the following two hypotheses

H1 Attitudes to research are different between male and female students

 

H2 Students, with previous research experience (e.g. undergraduate, field experience) will have a more positive attitude towards research, than students who have no previous research experience.

 

This will be achieved by running an independent ’t-test’. This is the most commonly used method to evaluate the differences in means between two independent groups.

 

The test variable for each t-test will be ‘total research attitudes’ and the grouping variable for hypothesis 1 will be ‘gender’ (Group 1 – 1(i.e. male; Group 2 = 2 (i.e. female). The grouping variable for hypothesis 2 will be ‘researchexperience’ (Group 1 – 0 (i.e. no; Group 2 = 1 (i.e. yes).

 

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Need Help-SPSS Data Analysis Assignment


Need Help-SPSS Data Analysis Assignment

Research Design and Statistics

SPSS Data Analysis Assignment Guide

Worth 30%

The SPSS Data Analysis Assignment gives you an opportunity to work with, analyse, and report psychological data. You have been provided with a data set from a study that examines how the size of an ostracising group influences individuals’ sense of belonging and self-esteem. At the end of this guide, you will find a skeleton lab report that includes introduction, method, and references sections. These sections give you more detail about the theoretical backgrounds, aims, and methodology, and can be directly copied into your report.

Note: Please refer to tutorial notes for SPSS (SPSS file is not the same shown in tutorial notes).

Here are some guidelines for how to complete this assignment

  1. Start by reading the introduction and method section provided at the end of this guide. This will give you background information about the study and details of the method. Think about how you would complete the hypotheses based on the information provided in the introduction section. Pay attention to the independent and dependent variables in the method section. Think about how you would test these hypotheses in SPSS.
  2. Open the data file in SPSS.
    1. Go into “variable view” and for each variable, put in a variable label and set the type of measure. Enter labels for the values as appropriate (when we need to know what each number means). Here is more information about the variables:
      • PartID is a participant ID number arbitrarily assigned by the researcher
      • Age is participants’ age in years
      • Gender is participants’ gender: 1 = male, 2 = female, 3 = other
      • Grpsize is size of the ostracising group: 1 = small group, 2 = large group
      • BELsc is the average of the 5 belonging items [I feel disconnected (reverse scored), I feel like an outsider (reverse scored), I feel that others interact with me a lot, I feel rejected (reverse scored), and I feel that I belong to a group]. Higher scores indicate higher levels of belonging.
      • SE1-5 are the five self-esteem items: [SE1-I feel good about myself, SE2-I feel insecure (reverse scored), SE3-I feel satisfied, SE4-My self-esteem is high, SE5-I feel liked]. For all items, higher numbers indicate higher self-esteem.

 

  1. Calculate a new variable that is the average of SE1-5. You don’t need to do any reverse scoring – it has already been done. Just average them together. Give this variable a meaningful label and adjust the scale of measurement as needed.
  2. Compute descriptive statistics for age and gender [M (SD) or N/n (%), as appropriate for each variable].
  3. Conduct the necessary assumption tests for the inferential statistics you plan to use.
  4. Conduct the inferential statistics that allow you to test your hypotheses (e.g., t-tests).
  5. Save your SPSS data (.sav) and output (.spv) files (NEED TO UPLOAD BOTH FILES)
  6. Calculate Cohen’s d for effect size (http://www.psychometrica.de/effect_size.html#cohen).
  1. Create a new Microsoft Word document for your assignment.
    1. Copy in the Introduction, Method, and Reference section from the end of this guide. You will add hypotheses to the introduction, participant information to the method, and then write the results and discussion section. The word limit for the new text you create (hypotheses, participants, results, discussion) is 800 words. The provided text does not add to this word count. The assignment should be presented in APA style (e.g., double-spaced, size 12 Times New Roman font), and it must use an appropriately formatted title page, headings, running head, tables and reporting style.
    2. Hypotheses: In your new document, remove the research questions text and write the research hypotheses. For research question 1, develop a hypothesis that states the expected difference in belonging for participants who were ostracised by the small and large groups. For research question 2, develop a hypothesis that states the expected difference in self-esteem for participants who were ostracised by the small and large groups. Remember to state your hypotheses in terms of operationalised variables.
    3. Participants: Add a participants section to the method that gives descriptive information about the sample. State how many participants took part in the study. Insert your paragraph summarising the characteristics of the sample under a Participants sub-heading within the Method section. Remember to use complete sentences when characterising the sample.
    4. Results: Report the results of your analyses in a Results section.
      1. Report the details of your assumption testing.
      2. Create a table to convey the descriptive statistics that map onto your inferential tests (M and SD for each DV at each level of the IV, n for each condition). Note that the table and its caption must conform to APA style. Never copy and paste a table from the SPSS output into your report.
  • Report the results of your inferential tests (t-tests), including the t-test statement and the effect size (Cohen’s d), and reference to the relevant means that you displayed in the table. You should not repeat the numbers that were presented in the table, in the text, but you may refer to them. In your Results section, link your hypotheses to your analyses (e.g., “To test the hypothesis that …., an independent-samples t-test was conducted comparing…”);
  1. Discussion: Interpret your results in a Discussion section. State the aim(s) of the study. Describe, summarise and explain the results. State whether the results are consistent with your hypotheses and the previous research summarised in the Introduction section you were provided. Provide some insight and explanation as to the relevance, importance, or implications of the findings in the context of the research questions. Identify any limitations of the study, and suggest some avenues for future research that directly follow from the limitations identified or results obtained. Finish your Discussion section with a strong concluding paragraph. You are not required to search for additional research articles.
  1. This report will be submitted electronically using the Turnitin link on the SPSS assignment section. You will need to submit three separate files in the appropriate tabs in turnitin.
  2. the electronic version of the report that is handed in (word or pdf file)
  3. The SPSS data file with all appropriate labels (.sav file)
  4. The SPSS output file with all output that is used in the report (.spv file)

 

SPSS Data Analysis Assignment Rubric

NN PA CR DI HD
SPSS data file (5%) Major errors/omissions in the scale of measurement, variable labelling, and/or value labelling.

OR

New variable not computed.

A major error/omission or many minor errors/omissions in the scale of measurement, variable labelling, and/or value labelling.

OR error in the computation of new variable.

New variable computed correctly. Minor errors or omissions in the scale of measurement, variable labelling, and/or value labelling. New variable computed correctly. A minor error or omission in the scale of measurement or variable labelling. All values labelled correctly where needed. New variable computed correctly. All scales of measurement specified correctly, appropriate labels provided for every variable, all values labelled correctly where needed.
SPSS output (10%) Inferential statistics are missing or incorrect. Inferential statistics are correct and complete, with a major error/omission or many minor errors/omissions in assumption testing and/or descriptive statistics. Inferential statistics are correct and complete, with minor errors or omissions in assumption testing and/or descriptive statistics. Inferential statistics are correct and complete, with a minor error or omission in assumption testing or descriptive statistics. All analyses (assumption testing, descriptive statistics, inferential statistics) are correct and complete.
Hypotheses (5%) Hypotheses are missing or incorrect. Hypotheses are partially correct. Hypotheses are mostly correct. Hypotheses are correct. Hypotheses are correct and clearly stated.
Results (40%) No results or substantially incorrect or incomplete results are provided, poor attempt to report results Incomplete descriptive and inferential statistics reported, consistent errors in reporting style Appropriate reporting with some errors or omissions in the reporting of descriptive and inferential statistics Appropriate and accurate presentation of descriptive and inferential statistics, all relevant information reported, description may lack clarity or precision at points Clear and accurate reporting of analyses (assumption testing, descriptive, inferential), good use of tables/figures
Discussion (30%) No discussion or very poor discussion providing incorrect interpretation, with results not linked to research question, inadequate conclusion Satisfactory discussion of results, may be inaccuracies in interpretation, some irrelevant or confusing information, conclusions may be weak Sound discussion of results in relation to research question/literature, generally appropriate interpretation of findings and conclusion matches research question, may lack clarity and include some inaccuracies in interpretation Good discussion of results relating to research questions/literature, good insight regarding interpretations and conclusions, may lack clarity at points Very well written discussion, appropriate reference to research questions/literature, excellent interpretation and understanding of findings, strong conclusion
Presentation (10%) Poor written expression, grammar and spelling, poor APA formatting Satisfactory writing style and presentation, with substantial room for improvement in writing style and APA formatting Most areas of presentation are good, may include some consistent errors in APA formatting Good written expression and grammar, may include some minor APA formatting errors Clear written expression, grammar and spelling. Formatting meets APA guidelines

SPSS Analysis


SPSS Analysis

1) For the variable HOME, what are the modes? Is the data normally distributed?

 

 

2) For the variable ARREST, what are the modes? Is the data normally distributed?

 

3) Why are we concerned about the distribution of data?

 

 

4) What difference does it make in the case of each of the variables (HOME and ARREST) if the data is not normally distributed?

All of the questions refer to the results of the SPSS analysis presented on pages 161-165 of the textbook.

Which is the download plus show your word use references

Answer by the number must be answer by number

 

Need Help-SPSS Project


 Need Help-SPSS Project

Follow all instructions carefully in presenting your answers. Be sure to show all your working. (Handwritten responses are fine.) You will not need SPSS for questions 1-3. For question 4, please download the housing dataset (from Latte), then import it into SPSS for analysis.

 

 

 

  • Jet Blue Airlines examined the bags of 80 passengers and found that 20% of the bags were overweight.

 

  1. Based on this sample, what is the 95% confidence interval for the proportion of bags that are overweight? [6 points]

 

  1. What is the minimum sample size the airline would need to estimate with 95% confidence to obtain a margin of error of +/- 3% for this estimate of the percentage of overweight bags? [6 points]

 

 

 

  • A factory recently took a sample to assess the quality of its candy output, looking at three different types of candy, and how many of each type of candy were damaged during the manufacturing process:

 

Candy # damaged Total # candies counted
Apple hard candy 15 50
Chocolate chew 18 50
Nut cluster 30 100

 

The factory management would like to determine whether the proportion of candy that is damaged is different for these three types of candy.

  1. Construct a contingency table for these data. [2 points]

 

  1. Is the proportion of candy that is damaged different for these three types of candy? (Calculate the appropriate statistic, give the p-value, and state your ) [6 points]

 

  • A manufacturer of headphones is interested in the sales of a particular headphone model in its stores in 8 airports. Some of these stores are located on the West and some on the East coast of the U.S. Also, the manufacturer recently conducted an advertising campaign. The sales before and after the advertising campaign, which it ran in February using billboards in the airports, are shown below (i.e., data for sales in those stores in January and data for sales in the same stores for )

 

(Some descriptive statistics have also been provided in the table. You will need to decide which ones you need for your calculations in answering the questions below.)

 

Store Location Sales in Jan Sales in March Change in sales
1 East coast 195 230 35
2 East coast 220 240 20
3 East coast 220 250 30
4 East coast 245 265 20
5 West coast 130 157 27
6 West coast 130 140 10
7 West coast 80 99 19
8 West coast 185 207 22
                                                  Summary statistics                                                   

All stores

Mean 175.63 198.50 22.88
SD 56.72 59.65 7.68
East coast      
Mean 220.00 246.25 26.25
SD 20.41 14.93 7.50
West coast      
Mean 131.25 150.75 19.50
SD 42.89 44.71 7.14

 

To get full points when answering each part below be sure to: calculate an appropriate statistic, state the result of the test, and state your conclusion.

  1. Looking at all the stores, is there a difference in sales between January and March? [6 points]
  2. Did the campaign have a different effect on sales for stores on the East coast versus on the West coast? [6 points]
  3. Was there a difference in sales in January for stores on the East coast versus on the West coast? [6 points]

 

  • Below are data for 40 houses located in one of two neighborhoods (A or B).

(This data is also provided in an Excel spreadsheet on the website for the class. Open the data in SPSS and conduct the analyses required to answer the questions. Be sure to paste output (i.e., tables) from SPSS into your answers where that is requested or else you will lose points.)

 

 

Neighborhood

Appraised Land Value Appraised Value of Improvements  

Sale Price

Has a yard? (yes/no)
A 56658 53806 255000 no
A 93200 11121 422000 no
A 76125 78172 290000 no
A 28996 5864 305900 no
A 30000 64831 118500 yes
A 30000 50765 93900 yes
A 46651 8573 191500 yes
A 45990 91402 184000 yes
A 42394 98181 168000 yes
A 47751 3351 169000 yes
A 63596 2182 208500 yes
A 51428 72451 264000 yes
A 54360 61934 237000 yes
A 65376 34458 286500 yes
A 42400 15046 202500 yes
A 40800 92606 168000 yes
A 12170 22786 375000 yes
A 24637 90598 169900 yes
A 30600 80858 135000 yes
A 44730 99047 176000 yes
B 38979 25946 140000 no
B 14861 59258 74900 no
B 14976 48957 57300 no
B 15244 55169 87500 no
B 18260 59267 82000 no
B 16680 55525 78000 no
B 53421 19792 175000 no
B 31417 99413 185000 no
B 32311 75343 123000 no
B 26817 78726 108000 no
B 24564 66533 108000 no
B 24564 71149 112900 no
B 27640 85347 106000 no
B 29656 78968 147500 no
B 13440 41177 61000 yes
B 45765 81227 320000 yes
B 16680 72867 99500 yes
B 17020 61935 93000 yes
B 25751 82259 110000 yes
B 25751 64568 100500 yes

 

 

  1. Give appropriate summary statistics (one measure of central tendency and one measure of

 

variation) for each of the 3 variables Appraised Land Value, Appraised Value of Improvements, and Sale Price, calculated separately for neighborhoods A and B. Important: PROVIDE ONLY ONE (APPROPRIATE) CENTRAL TENDENCY MEASURE AND ONE (APPROPRIATE) MEASURE OF VARIATION FOR EACH VARIABLE FOR EACH NEIGHBORHOOD. [6

points]

 

  1. Based on this data sample, do neighborhoods A and B differ in the number of houses with and without yards? In your answer be sure to calculate an appropriate statistic, state the result of the test, and state your (Paste the output from SPSS for the statistical test that you do in your answer, as well as stating your conclusion and writing out the appropriate statistic that supports your conclusion.) [6 points]

 

  1. Based on this data sample, do houses in neighborhoods A and B have different sale prices? (In your answer be sure to calculate an appropriate statistic, state the result of the test and state your conclusion.) (Paste the output from SPSS for the statistical test that you do in your answer, as well as stating your conclusion and writing out the appropriate statistic that supports your conclusion.) [6 points]

 

  1. Provide a correlation matrix for Appraised Land Value, Appraised Value of Improvements and Sale Price for neighborhood B only (you will need to split the data to do this – in SPSS under the Data menu use the “split file” command, split by neighborhood, and select “organize output by groups”). In words, explain the meaning of the correlation between Sale price and Appraised Land Value and the meaning of the correlation between Appraised Land Value and Appraised Value of Improvements. [6 points]

 

Note: make sure you deselect “split file” after doing this question part, so that you analyzing all the cases for the next two parts.

 

  1. Imagine you are interested in the relationship between house Sale price and Appraised Land Value while controlling for any effects of Appraised Value of Improvements. Conduct a linear regression that allows you to test this relationship (using data for all the houses, i.e., from both neighborhoods). State your conclusion about the relationship, and provide the statistics that support your (Paste your SPSS output for this regression into your answer.) [6 points]

 

  1. Imagine you are interested in the relationship between house Sale price and Neighborhood, while controlling for any effects of Appraised Land Value and Appraised Value of Improvements on Sale price. Conduct a linear regression that allows you to test this relationship. State your conclusion about the relationship, and provide the statistics that support your conclusion. (Paste your SPSS output for this regression into your answer.) [6 points]

 

 

Excel Data

Neighborhood Appraised Land Value Appraised Value of Improvements Sale Price Has a yard? (yes/no)
A 56658 53806 255000 no
A 93200 11121 422000 no
A 76125 78172 290000 no
A 28996 5864 305900 no
A 30000 64831 118500 yes
A 30000 50765 93900 yes
A 46651 8573 191500 yes
A 45990 91402 184000 yes
A 42394 98181 168000 yes
A 47751 3351 169000 yes
A 63596 2182 208500 yes
A 51428 72451 264000 yes
A 54360 61934 237000 yes
A 65376 34458 286500 yes
A 42400 15046 202500 yes
A 40800 92606 168000 yes
A 12170 22786 375000 yes
A 24637 90598 169900 yes
A 30600 80858 135000 yes
A 44730 99047 176000 yes
B 38979 25946 140000 no
B 14861 59258 74900 no
B 14976 48957 57300 no
B 15244 55169 87500 no
B 18260 59267 82000 no
B 16680 55525 78000 no
B 53421 19792 175000 no
B 31417 99413 185000 no
B 32311 75343 123000 no
B 26817 78726 108000 no
B 24564 66533 108000 no
B 24564 71149 112900 no
B 27640 85347 106000 no
B 29656 78968 147500 no
B 13440 41177 61000 yes
B 45765 81227 320000 yes
B 16680 72867 99500 yes
B 17020 61935 93000 yes
B 25751 82259 110000 yes
B 25751 64568 100500 yes

Need Help-SPSS Project

Cell Phones Apps Communication


 Cell Phones Apps Communication

Results and discussion write-up (75 points):

After data collection takes place, students will be required to analyze the data and describe what the results are. Students will also be required to interpret the findings and figure out what the results mean for the topic studied. There is no required page limit, but the paper should be around 4-6 pages. The basic outline should be:

  1. Results
    1. Descriptive statistics:
      1. How many subjects were included?
      2. What are the mean, standard deviation, variance, and standard error of the mean for each variable?
    2. Inferential statistics:
      1. What statistical tests were used? Why (i.e., what does the test do that makes it appropriate)?
      2. What are the calculated value of the statistic (i.e., the t-value, r-value, chi-square value), the degrees of freedom, and the calculated p-value? (If more than one statistical test is performed, these should these should be reported for each test.)
  • Is the finding statistically significant? What does this mean?
  1. Discussion
    1. What do the results mean? What do the results tell us about the topic being studied?
    2. How do the results help us to understand communication?
    3. What explanations for the results can you think of? Do they fit with what other authors found, based on the literature that was discussed in class?
    4. What are some limitations or weaknesses of the study?
    5. What would a good next step be for continuing to study this topic?

 

Results and discussion write-up grading guidelines:

  • Results (35 points):
    • All descriptive statistics listed in the outline are provided (2 points each, 10 points total)
    • An explanation of the inferential statistics used is included, and the explanation for why is consistent with the explanation of those tests given in class (10 points)
    • The calculated value, degrees of freedom, and p-value are reported for all tests (10 points)
    • Whether or not the test is significant is correctly reported for each test (5 points)
  • Discussion (35 points):
    • All five questions in the outline above are answered thoroughly (7 points each)
  • Grammar and spelling (5 points)

 

 

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