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TAKS 1 & 2 Guidelines for Data Collection and Analysis

Task 1 (20%)

TAKS 1 (20%) – in this part, you are asked to describe where did you get your data from, how did you prepare your dataset, describe the dataset, and comment on the overall quality of your data. (Students who submitted their first draft of Task 1 should include the improved version and submit it together with Task 2.)
How to submit? There will be a submission point on Moodle. 
What to submit? Data file (Excel file or Stata data file) and your answers either in MS Word or PDF (PDF is better). You are asked to submit the final datafile (not the original data file).  

1.1.    Introduction to your dataset

a.    Insert the link to the dataset from where you downloaded it. Briefly describe the source of your data (e.g., the data is from National Statistical Office of Canada, it was collected as a part of Census, and it focuses on fertility rates in Canada). If you use MS Excel, describe whether and how you adjusted the data. If you use Stata, do not forget to copy the command history. 
i.    If you decided to use the data uploaded on Moodle, write “I have decided to use the data entitled …”. 
ii.    If you decided to use data given to you in a different module (but you did not download them yourself), write here in which module you used the data. 
iii.    If you collected your own data, state the details here – how did you get in touch with your respondents, do not forget to include your questionnaires at the end. Describe if you faced any issues during the data collection. When and how did you collect the data (emails, phones, in person, etc.) 

1.2.    Preparation and description of your data 

a.    Prepare your data – make sure you delete empty rows, or rows containing some summary statistics (like we practised in week 1 Lab sessions). In this section, describe all your steps if you use MS Excel or copy the entire command history into section 4 – see below. 
b.    Understand your data
i.    Answer in words: What type of dataset do you have? How many observations do you have? How many variables do you have? Create a table which would describe the variable names, the variable description, variable type, the units of measurement, the number of observations and the number of missing observation
Note: you do not need to comment on “the mean value of my variable is …” because it is written in the table. Focus here on the intuitive interpretation of your variables. Think about how these measures altogether describe your variable (especially, its distribution). 
ii.    Pick three variables and show visually their distributions (i.e., I need three figures here). Select the most suitable way to visualize the distribution of the variables. Comment on it using the descriptive statistics measures (i.e., look at the descriptive statistics and discuss how they are in line with what the figures show you). Note: save the figures from Stata (use “Save As” and select .png format. Try to include the title to each of your figure. 

iii.    Construct correlogram (or correlation matrix) using all your variables. Comment on the results. Note: you can directly copy-paste correlogram (correlation matrix) from Stata. Comment on pairwise correlations. 

1.3.    Comment on the overall quality of data. Write an intuitive description of your data. 
Hints: you may think about the following questions: Do you have information how the data was collected? Do you see many missing observations (in 1.2.b you were asked to record the number of missing observations to the table, here you are asked to use that information to discuss the quality of your data)? If yes, which variables contain missing observations? Does it represent any problem for your analysis? Also think about potentially missing variables in your data – would that represent any problem for your analysis? 

TASK 2 (20%)
In this part you should focus on your research question, proceed with analysis, and write a short report. Think about the most suitable model for your analysis. 

2.1.    State your research question (e.g., I want to study whether there are gender differences in Math scores). 
2.2.    What is your dependent variable? 
2.3.    Which independent variables do you plan to use in your regression? Prepare a table in which you describe the expected sign of the estimated coefficient, you explain why you expect that sign, and why did you decide to include that variable in your regression

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