STUDY ONE METHODS, RESULTS DISCUSSION INSTRUCTIONS1 STUDY ONE METHODS, RESULTS DISCUSSION INSTRUCTIONS 1 Instructions for Paper II: Study One Methods, Results, and Discussion (Worth 35 Points) Ryan...

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STUDY ONE METHODS, RESULTS DISCUSSION INSTRUCTIONS1 STUDY ONE METHODS, RESULTS DISCUSSION INSTRUCTIONS1 Instructions for Paper II: Study One Methods, Results, and Discussion (Worth 35 Points) Ryan J. Winter Florida International University Instructions for Paper II: Study One Methods, Results, and Discussion (Worth 35 Points) Purposes of Paper II: Study One Methods, Results, and Discussion 1). Psychological Purpose The psychological purpose behind Paper II is to make sure you can tell your reader what you did on your study, how you did it, and what you found. By now you have read several empirical studies in psychology, and you should be familiar with the Methods, Results, and Discussion sections. Now is your chance to write the Methods, Results and Discussion! Like the studies you looked at for Paper I, you will provide information about your participants, materials, and procedure in your Methods section. Your participant section goes first, and it includes descriptive statistics about your sample (means and standard deviations for age as well as percentages for gender and race/ethnicity). Your materials and procedure sections include information about what you did and how you did it. You should write this section for an audience who is unfamiliar with your specific study, but assume that they do know research methods. Thus educate your reader about your materials and procedure, giving enough detail so they could replicate the study. This includes explicitly describing your independent and dependent variables and talking about how you presented those variables to your participants. My suggestion is to look over the articles you summarized in Paper I and see how they wrote their Methods. This will give you a good idea regarding the level of depth and detail you need in your own Methods section. Your Results section follows. The purpose of this section is to make sure you can show how you analyzed the data and describe what you found. You will have a lot of help in this section from your lab materials (especially your lab powerpoint presentations). Finally, I want you to include a short discussion of your findings. Tell me if you supported or did not support your hypotheses and explain why you got those results (you can actually speculate here if you like, but make it “educated” speculation!) 2). APA Formatting Purpose The second purpose of Paper II: Methods, Results and Discussion is to once again teach you proper American Psychological Association (APA) formatting for these sections. In the pages below, I will tell you how to format your paper using APA style. There are a lot of very specific requirements in APA papers (as specific as what to italicize), so pay attention to the instructions below as well as the APA formatting lecture presentation! 3). Writing Purpose Finally, this paper is intended to help you figure out how to write a Methods, Results, and Discussion section. Many students find statistics intimidating, but my hope here is that writing this paper will help you understand both the logic and format of statistics in results sections. We will once again give you a lot of feedback and help in this paper, which will be able to revise for your Papers IV and V later in the course. Make sure that you write this for an audience familiar with APA methods and results, but also for someone who needs you to tell them what you found. Note #1: The plagiarism limit is higher in this paper (up to 65%) since your classmates are doing the same design. Do not go higher than that, though! 65% is the maximum allowed! Note #2: You do NOT need to include your literature review / hypotheses in Paper II, as Paper II focuses just on your methods, results, and discussion. However, you will include those Paper I components later in Paper III, so do keep them handy! Again, sorry for the length of the instructions! They are long, but take it one section at a time and you will get all of the content you need for your paper. It also increases your chances of getting a great grade! Instructions for Paper II: Study One Methods, Results, and Discussion (Worth 35 Points) 1. Title Page: I expect the following format (1 point): a. The title page for your Paper II is identical to the one you used for Paper I: Literature Review Study One. For proper APA formatting, either copy your title page from Paper I or review the title page instructions I gave you in Paper I. You can change your title if you like, but make sure it helps to describe your study (much like a title in PsycInfo describes what the authors did in their paper) 2. Abstract? a. You DO NOT need an abstract for Paper II: Methods, Results, and Discussion (Study One). You cannot write it until you run both study one and two, so omit it for now 3. Methods Section: I expect the following format (15 points): a. For this paper, the methods section starts on page 2. b. Write Method at the top of this page, make it bold, and center it (see the top of this page as an example!) c. The participants section comes next. The word Participants is bolded and left justified. In this section … i. Tell me who your participants were (college students, family members, friends?) and how many there were. 1. Note: If a number starts a sentence, then spell out the number. That is, “Two-hundred and five participants participated in this study.” 2. If a number is mid-sentence, you can use numerals. “There were 205 participants in this study.” 3. But keep numbers consistent. If you spell out a number at the start of the sentence, carry that through and spell out other numbers in the sentence. 4. For statistics, always use numbers (M = 5.43, SD = 1.12, 67%, etc.) 5. For scales, always use numbers, too (1 = Strongly Disagree to 6 = Strongly Agree) ii. Provide frequencies and descriptive statistics for relevant demographics. 1. For some variables—like ethnicity and gender—you only need to provide frequency information (the number of participants who fit that category). “There were 100 men (49%) and 105 women (51%) in the study.” Or “The sample was 49% male (N = 100) and 51% female (N = 105).” 2. Other variables—like age—are continuous (rather than categorical), so use descriptive statistics here (the range, mean, and the standard deviation). “Participants ranged in age from 18 to 77 (M = 24.01, SD = 3.50).” or “The average age of participants was 24.01 (SD = 3.50).” You can find out how to get this information by reading the lab powerpoint and the crash course quiz documents 3. Make sure to italicize the N, M, and SD (the letters, not the numbers) iii. Make sure to include a “callout” to the table. That is, write “See Table 1” at the end of the participant section to direct readers to your demographics table. d. Materials and Procedure i. For this section, things are flexible. Some studies include Materials and Procedure in the same section while others break them up into two sections. This is a matter of choice. 1. In general, the more complex the design, the better it is to split up the materials and procedure. In one section, the author may describe the materials; in the next, they describe what participants did with those materials (procedure). This is one option for you. However … 2. However, your “Paper II: Methods, Results and Discussion (Study One)” is simple enough that I strongly recommend combining them into one overall Materials and Procedure section. The rest of this section focuses on combining the Materials and Procedure … ii. The words Materials and Procedure are flush left. In this section, provide information about your materials and your procedure. I suggest starting with the procedure and discussing the materials in the order in which participants saw them. That is, tell your reader what your participants did in the order that participants did them. Be specific here. 1. First, talk about the oral informed consent procedure. 2. Second, talk about the three versions of the Fear of Missing Out (FoMO) questionnaires. Provide enough detail so that your readers know how the three conditions differ. Imagine I do not know what you did, but I need to able to replicate your design. YOU need to give me enough detail so I can do so. a. I want to stress this “detail” concept – Pretend that I have no idea what you did or what your materials look like, but I want to replicate your study. Thus, teach me your design and your procedures. Be VERY clear and detailed about what you did and how you did it so I can replicate your study design. b. Go into painstaking detail about what EACH section of the survey page looked like, including what the participant instructions say and the look of the stimulus materials. If there are advertisements on the page, describe them. If there are pictures, describe them. If there is a profile, describe it. If these items are identical across all conditions, note that fact. c. Importantly, describe how the surveys differ. That is, you have three versions of the survey, with the main difference in the number of other friends who can attend the event (none can attend, some can attend and some cannot, or all can attend) d. Note: At the end of the semester, someone other than your instructor / TA may grade your final paper. They may know NOTHING about FoMO, but they do know methods. Write this section for that methodology expert (but topic novice). 3. Third, talk about your dependent variables (that is, your survey questions. For these dependent variables, once again provide enough detail so I know exactly what questions you asked. For example, “Participants provided their gender, age, and race”. For other dependent variables, tell me how the responses were recorded (yes/no, true/false, a scale of 1 to 6, etc.). If you used a scale, note the endpoints (your reader needs to know whether a higher number is better / worse than a lower number). For example, “Participants were asked, ‘How frustrating was this task?’, and they responded on a scale from 1 (very frustrating) to 6 (not at all frustrating).’” a. Your study has a few really important DVs (including several DVs about how the participants feels about missing out Part
Answered 4 days AfterNov 19, 2021

Answer To: STUDY ONE METHODS, RESULTS DISCUSSION INSTRUCTIONS1 STUDY ONE METHODS, RESULTS DISCUSSION...

Mohd answered on Nov 23 2021
129 Votes
Paper II: Study One Methods, Results, and Discussion
Participants:
Initially in this sample 155 respondents were included. There were few outliers or wrongly coded observations, so I have removed those observations from our sample. Now total number of observations is 136 in our sample. Now the proposed sample size for this research will be 136. To examine relationship according to no less than 50 participants for correlation or regression with the increasing number of large numbers of independent variables.
For proper analysis of the data collected from survey process, SPSS abbreviated for Statistical Package for the Social Sciences has been introduced. SPSS has been the most widely used statistical software that meets the purpose of statistical analysis in terms of social science as well as market analysis. The usage of SPSS
20 software has been extremely beneficial during the analysis process as this software tool is exceedingly powerful for appropriate manipulation as well as deciphering data from survey process.
In case of missing values, IBM SPSS 22 software has default feature of listwise deletion. In IBM SPSS we have two methods of deleting the missing values listwise and pair wise. List wise deletion is only appropriate in the case when we have missing data distributed.
This study conducted by gathering only primary data through questionnaire. The questionnaire design was based on the objective of the study. There were four parts in our questionnaire as demographics, Fear of missing out (FOMO) and others respectively. There were no missing values in our dataset. We have no missing values in our dataset. As per the available literature, missing values should be less than 5 percent.
Our first task in quantitative analysis will be descriptive analysis, so we have conducted descriptive analysis on respondent’s demographic information. Quantitative research approach is appropriate one while examining the relationship or association between variables.
Methods
Validity Analysis
The extent to which we correctly measure a construct known as validity. (Dillon, Madden, & Firtle, 1994). In our study we have used discriminant validity and convergent validity to assess the construct validity (Hair, Black, Babin, & Anderson, 2010). Assessing the tendency to which measurement of a factor are correlated; discriminant validity was assessed by measuring the degree to which conceptually similar sub-dimensions are distinct. Our all the construct are unidimensional. Each construct item headed towards same direction. All construct items were measured at the same scale. Henceforth, for the second-degree concept (i.e., five sub-dimensions of fear of missing out (FOMO), the summated scale of the five sub-dimensions showed that the five sub-dimensions related with, but unique to each other.
Reliability Analysis:
An important measure is accuracy of a research instrument, also known as reliability. How accurately is measure in regenerated with repetitions in measurement. (Dillon, Madden, & Firtle, 1994). The reliability was measured using Cronbach coefficient alpha. All the construct has reliability greater then traditionally suggested of 0.70 (Nunnally, 1978). Construct fear of missing out (FOMO) has Cronbach alpha value of 0.730.
    Construct
    Number of items
    Cronbach’s Alpha
    Fear of missing out (FOMO)
    5
    0.730
Demographics:
· Of the total respondents, 86 % are FIU students and 14 % are Non FIU students.
· Of the total respondents, 26.5 % are Caucasian, 50 % are Hispanic, 1.5 % are native Indian, 11.8 % are African American, 2.9% are Asian American and 7.8% are in others group.
· Of the total respondents, 30.1 % are English speaker and 69.9 % are in a relationship.
· Of the total respondents, 25.7 % are attention check (All), 47.8 are with attention check (None) and 26.5 % are with attention check (Some).
· Of the total respondents, 29.1% are with single relationship status, 70.90% are in relationship.
· In female respondents, 23.2% are with single relationship status, 76.8 % are in relationship. On the contrary in male respondents 35.4 % are with single relationship status, 64.6 % are in relationship.
· Of the total respondents, 83.8 % are English speaker and 16.2 % are non-English speaker.
· Of the total English speaker, 52.7% are male and 47.3% are female. Of the total non-English speaker 27.3% are male and 72.7% are female.
Testing the theoretical framework
Chi Square test:
Generally, in psychological research, we end up gathering scores from members. This information are normally consistent measures, and may be scores on a survey or psychological scale, response time information or memory scores, for model. Furthermore, when we have such an information, we will for the most part use it to search for mean contrasts on scores between or inside gatherings (for example utilizing t-tests or ANOVAs), or on the other hand maybe to search for connections between various sorts of scores that we have gathered (for example connection, relapse).
Anyway, here and there we don't have such an information. Some of the time information will be a ton more straightforward than this, rather comprising just of recurrence information. In these cases members don't contribute scores for investigation; rather they each add to a "head count" inside various gathering classes. Such an information is known as discrete information, instances of which could be sex (male or female) or college degree orders (1, 2:1, 2:2, 3, pass or fall flat) – or some other variable where each member falls into one classification. At the point when the information we need to examine is this way, a chi-square test, signified χ², is normally the proper method.
Chi-square is utilized to test speculations about the circulation of perceptions in various classes. The invalid speculation (Ho) is that the noticed frequencies are as old as anticipated frequencies (with the exception of chance variety). Assuming the noticed and expected frequencies are something very similar, then, at that point, χ² = 0. On the off chance that the frequencies you notice are not quite the same as anticipated frequencies, the worth of χ² goes up. The bigger the worth of χ², the more probable it is that the circulations are fundamentally unique. To attempt to clarify this a little better, we should ponder a substantial model. Envision that you were keen on the connection between street car crashes and the age of the driver.
We could haphazardly acquire records of 60 mishaps from police documents, and perceive the number of the drivers fell into every one of the accompanying agecategories: 17-20, 21-30, 31-40, 41-50, 51-60 and more than 60. On the off chance that there is no connection between mishap rate and age, then, at that point, the drivers ought to be similarly spread across the diverse age-groups (for example there ought to be comparative quantities of drivers in every class). This would be the invalid speculation. In any case, in case more youthful drivers are bound to have mishaps, then, at that point, there would be countless mishaps in the more youthful age-classifications and a low number of mishaps in the more established age-classifications.
Correlation coefficient
The sole purpose of correlation coefficients is to evaluate strength of relationship between two continuous variables. There are three methods to evaluate correlation coefficients Pearson, Spearman, and Kendall. Generally, we use Pearson correlation in linear regression. Correlation coefficients vary from -1 to 1. Negative correlation coefficient (coefficient value between -1 to 0) indicates inverse relationship between variables. Positive correlation (coefficient value between 0 to 1) coefficient indicates direct relationship between variables.
Dependent variable:
The change in dependent variable depends on independent variables. If we examine children's age and height. Height will be a dependent variable and age will be an independent variable. As we know, if we increase the age, the height of the child is likely to be higher. Child age does not depend on any variable except itself. In our analysis we have considered FOMO Combined as our dependent variable. That has the average of all FOMO construct responses.
Independent variable:
If we examine children's race and height. Height will be a dependent variable and race will be an...
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