1) Descriptive Statistics
a) Central Tendency: Mean, median, mode
b) Variation: std dev, variance, CV = sd/mean
b) Shape: skewness using histograms: hist()
2) Normal distribution
a) Area finding under the curve: Probabality
of some event. e.g. if we randomly pick up a person
from this group, what are the chances, this person’s
age > 25, or salary < 75000, or weight between 150 and
170 lbs. ==> pnorm()
b) Area is given. We wonder cutoff point(s) for area.
==> qnorm()
3) Confidence Intervals
LowerLimit < mu < UpperLimit
LowerLimit = xbar – z*sd/sqrt(n)
UpperLimit = xbar + z*sd/sqrt(n)
90% confidence level -> z=1.68
95% confidence level -> z=1.96
99% confidence level -> z=2.58
For example: qnorm(0.95) = 1.68
4) Hypothesis testing – One sample
Two sided (mu = A or not)
a) Construct your hypothesis
H0: mu = A
Ha: mu != A
b) i) Calculate zcrit and zstat using formulas.
Sketch and look at zstat’s position in the distribution.
ii) Use t.test() function. Look at the pvalue.
5) Hypothesis testing – One sample
One sided (mu > A or not)
a) Construct your hypothesis
H0: mu <= A
Ha: mu > A
H0: mu >= A
Ha: mu < A
b) Same procedure as in two sided except
don’t divide alpha by 2.
If question is “>”, shade the right tail.
If question is “<“, shade the left tail.
6) Hypothesis testing – Two samples
a) Paired t-test: t.test(…, paired = TRUE, ..)
b) Equal variances: t-test(…, var.equal = TRUE,..)
c) Seperate variances t-test: t-test(…, var.equal = FALSE,..)
Look at the pvalue, if it is less than alpha/2, then reject H0.
7) z-test for proportions
One categorical variable. Test claims about the proportion
of one category. e.g. Proportion of voters supporting
candidate A is equal to 55%.
Majority: 50% or more supporting candidate A.
8) Chi-Square test for independence
Two categorical variables. Test if these two variables
are independent or not. Use the chi.square() and look at pvalue.
If pvalue < alpha, reject H0 which says they are independent.
9) ANOVA F test
One numerical and One categorical variable.
You are testing if the mean of the numerical variable differentiate
along the categories of the categorical variable.
H0: mu1 = mu2 = mu3 …. = mun
Ha: At least one mean is different.
Use function aov() and look at pvalue to see if you can reject H0.
10) Linear Regression
Simple Lin. Regression: Y = b0 + b1*X
Multiple Linear Regression: Y = b0 + b2*X1 + b2*X2 + … + bn*Xn
Calculate b coefficients using lm() function.
Make sure the model is a good fit.
Understand what each coefficient means.
 
Onlinestudyguide

Instructions:

• 7-9 pages (12-point font, Times New Roman, 1-inch margins, double-spaced, with headings).
• Introduction: A description of the problem or issue
  • Hook the reader with a problem / issue / statement of why this topic is relevant.
    Describe the problem / issue / topic
    Explain what other researchers have found about the topic
    Describe what your paper contributes (i.e. an overview and analysis of XXX) and why that is interesting.

• Background: The context / countries involved; historical context where relevant
  • Describe the context of your topic
    What countries are involved?
  • What is the relevant historical context?
  • If your topic is a marketing strategy, provide some company background and historical context for the globalization of the company – where they are headquartered, where they operate, etc.

• Analysis: An analysis of the problem or issue using tools and concepts (tariffs/agricultural trade).
  • Relevant data or statistics to support your analysis
  • References to at least 2 peer-reviewed journal articles relevant to the topic or analysis
  • include numerical data, graphs, and figures to support your analysis and discussion.

• Discussion and conclusion
  • Provide concluding remarks for the paper. Link the findings and conclusion back to your statements in the introduction.

• Citations and References

Include at least 2 peer-reviewed journal articles related to the topic or analysis Use in-text citation (author, date)
Include a references page
Project Topic: How Brexit is affecting international agriculture trade.
1) A brief description of the problem/issue:  
The UK have been a part of the European Economic Community since 1973. However, the UK had always maintained a distance from the EU. It has its own currency and refrained from joining the Schengen agreement which removes internal border controls within the EU.
Brexit (British Exit) is the withdrawal of the United Kingdom from the European Union on January 31, 2020. The process began on January 23, 2016 when the UK voted to leave the EU. The residents decided that the benefits of belonging to the unified monetary body no longer outweighed the costs of free movement of immigration. As a result of this exit, the new trade agreement could raise tariffs and cause inflation. Tariffs will be imposed on imports between the UK and EU and raise the cost of exports. This would hurt UK exporters as their goods become more expensive in Europe.
 2) a brief discussion of how the topic relates to food and agriculture
The UK and the EU share an important agri-food trading relationship. EU countries export large volumes of agri-food products to the UK, notably fresh and processed fruits and vegetables, meat products, and food preparations. In 2017, the value of these exports came to 40 billion. The withdrawal will interrupt the food supply, large impacts on the British food system and diet-related risk factors because the majority of the domestic demand for fruits, vegetables, and some meats, is currently met by imports.
3) a discussion of how you propose to analyze the problem/issue (i.e. what course concepts or tools will be used, is there data available, etc.).
I will be adding tables, graphs, and charts that projects the tariff/non-tariff measures applied by Brexit. As well as figures to provide actual statistics about the impacts of Brexit on both local/international trade.
Reference:
Amadeo, K. (2020, March 14). Brexit Consequences for the U.K., the EU, and the United States. Retrieved November 21, 2020, from https://www.thebalance.com/brexit-consequences-4062999
EU agriculture and the withdrawal of the United Kingdom from the EU. (2020, March 15). Retrieved November 21, 2020, from https://ec.europa.eu/info/food-farming-fisheries/farming/eu-agriculture-and-brexit_en
Hubbard, C., Davis, J., Feng, S., Harvey, D., Liddon, A., Moxey, A., . . . Wallace, M. (2018, August 23). Brexit: How Will UK Agriculture Fare? Retrieved November 21, 2020, from https://onlinelibrary.wiley.com/doi/full/10.1111/1746-692X.12199