Collecting and organizing your data

Collecting and organizing your data

As you learned in class, random samples are unbiased and allow one to study the sample and learn about the population. When it come to your final project here are some recommendations about how to approach sampling.
Use a sample size between 30 and 50. Although the professional pollsters usually use a sample size of approximately 1000, this is not reasonable in an elementary statistics course.
Consider using a convenience sample. Although professional pollsters use random samples to avoid bias, it is not reasonable to perform a random sample of a large population in an elementary statistics course.

Section 1: Background: Provide background information on your topic. This may involve giving a historical perspective and/or summarizing the results of previous research.

Section 2: Data collection: Create a survey (include a mix of numerical and categorical variables) or design an experiment to answer your fundamental question. If conducting a poll, discuss whether or not you have used a random sample. If you have not used a random sample, clearly state the limitations of your poll. If you are conducting an experiment, be sure to clearly state how randomization was used.

Section 3: Data analysis: Apply the data analysis techniques learned this semester. Here is a brief summary of some of these techniques. You will not need to use all of these techniques. The key is to choose the techniques which best address your fundamental question.

Descriptive Statistics:

Numerical variables: Create stemplots, histograms, boxplots, compute five number summaries, mean and standard deviation.
Categorical variables: Create pie charts and bar charts. Also, categorical variables may be used to make comparisons. For example, in my caffeinated beverage survey, I could use the students resident/commuter status to form two groups; residents and commuters. I could then compare the caffeine consumption of the two groups using side by side boxplots. In StatCrunch, consider using Data/Split Columns when you need to separate numerical varaibles by category.
Inferential Statistics

Numerical variables:
Confidence intervals for means and significance tests including 1-sample t-test, 2-sample t-test and ANOVA.
Categorical variables: Confidence interval for proportions and significance tests including 1-proportion and the chi-square test for independence. Again, categorical variables may be used to make comparisons. For example, in my caffeinated beverage survey, I could use the students resident/commuter status to form two groups; residents and commuters. I could then compare the caffeine consumption of the two groups using a 2-sample t-test. This would complete the comparison initiated with the side-by-side box plots.

Section 4: Conclusion: A paragraph (page at most) summarizing your project (regrets, key findings,…)

 
College Student Social Media Habits
Olivia Grant
Professor Manthey
Elementary Statistics
Social Media Questionnaire
Rough Draft

1. What do you hope to accomplish with social media?

I. Networking _____
II. Build Credibility _____
III. Create a Community____
IV. Market Events_____
V. Other ______

2. What Social Media are you using?
I. Facebook ___
II. Twitter ____
III. Instagram___
IV. LinkedIn ___
V. Snap chat ___
3. How many hours per day are you committing to Social Media?
I. One ______
II. Two_____
III. Four _____
IV. Eight ____
V. Other ____
4. How many days of the week are you on any of the above Social Media?
I. One ___
II. Two ____
III. Three____
IV. Four____
V. Five ____
VI. Other ____
5. What is your Major? _____________
6. Are you a Resident ________ or Commuter ________
7. What is you class year?
I. Freshman ______
II. Sophomore _____
III. Junior _____
IV. Senior_____
8. How do you gain access to the different Social Medias
I. Smartphone____
II. IPad / Tablet ____
III. IPod/IPod touch ____
IV. Laptop /Desktop Commuter_____
9. On a scale of 1-10 (1 = very poor and 10 being very excellent), how would you rate your overall Social Media Habits? _________

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