PSEM: Research Report Data AnalysisMarketing Research and Data Analysis
The next two weeks of content are essential for your second assessment. You will be analysing and reporting the data collected for your research report assessment (worth 40% of your grade for PSEM). At the end of these two weeks, you should be in a position where you have everything you need to be able to write the method and results section of your report. Rather than provide fillable text-boxes, I have left this assignment document open (as students can write as many or as few notes as they like)
Begin by taking a copy of the data file from Blackboard (located in the Research Report Assignment 2 folder). Save this folder somewhere secure on your computer. Do not save straight to a thumb drive. You will want to get into the habit of saving regularly. I also recommend that you save a new file each time – saving over an old version and realising you have made a mistake makes it very difficult to recover work! You should also remember you need to save both your output and datafile; saving one will not save the other.
Now you have the datafile open, you should see a well-organised datafile containing over 100 different variables. Take a minute to familiarise yourself with these variables and the responses to each. Note that this datafile was a lot messier to start with. This version of the datafile has been screened, cleaned, and with incomplete/missing/nonsense responses removed. This is also detailed elsewhere in the Research Report Assignment 2 folder.
First, let us gather the demographic information that will need to be reported in the Participants section of the report. While some studies may have many demographic variables, we will keep it simple and limit the demographic information to participant age and gender. Highest level of education is not required given that this entire sample were university students. In the future this variable will be useful when we administer this survey to the public.
- Calculate and report the appropriate summary statistics for age and gender (e.g., measures of central tendency, dispersion, frequency counts etc.). Also work out the total number of cases in the data file and by group:
As detailed in the assessment guidelines, you will be required to test two hypotheses. This next section focusses on hypothesis one. The question that I am asking students to address is the following: “Does labelling a child with a mental health condition impact people’s belief about help-seeking behaviour? (regardless of the specific condition)” (Note. This is not a research question [yet]).
- Based on your understanding of previous research and our data file, develop ONE testable hypothesis. This is the first hypothesis that you will use in your research report. Feel free to check the appropriateness of this hypothesis with your tutor in-class or on Discussion Board.
- What is the IV and DV for this Hypothesis? What Statistical Test will you use to test this Hypothesis?
- Before you can test this hypothesis, you need to ‘compute’ some new variables. That is, you will need to calculate an average Help-Seeking Beliefs score. This is because the Help-Seeking Beliefs scale is made up of four separate items (10 to 13 on the stigma scale). We want an average score before we can move further. To do this, you will need to go to Transform à Compute Variable and input a formulate for an average score. Write your formula below. (Remember, you will have to do this three times – one for each mental health condition). Remember we are asking you to calculate an average score (i.e., you will have to total the items and then divide by the number of items for this variable).
- Once you have your three Help-Seeking Belief scale scores, we can then calculate the average Help-Seeking Belief scale scores for each participant’s three responses – we are ignoring mental health conditions for this test. You will only need to calculate this once. Remember we are asking you to calculate an average score (i.e., you will have to total the items and then divide by the number of items for this variable). Note this formula below.