Excel (Page)
1 Describing data
1.1 A taxonomy of data types
1.2 What is a "data set"?
1.3 Frequency
010 Microsoft Excel basics - preparing tables and entering formulas.xlsx 221 Rec 1
020 Preparing histograms using COUNTIF to describe data.xlsx 221 Rec 1
1.4 Representation of distributions
1.5 Measures of central tendency
1.6 Measures of dispersion
Self study Income distribution in Türkiye
221 Handout 240214 - Mean - Variance - Covariance.pdf 221 Rec 2 Brief review of handout
030 Use of PERCENTILEs to describe data.xlsx 221 Rec 2
1.7 Measures of association for bivariate data
1.8 Issues of unit and scale
1.9 Chebyshev’s theorem (Chebyshev’s inequality)
1.10 Adding and multiplying terms over an index
040 Generating random numbers - Linear Cogruential Generator - Using the digits of Pi.xlsx 221 Rec 3
050 Describing data via histograms to reveal Global warming using COUNTIFS.xlsx 221 Rec 4
221 Hw1 due 20 October 2025 Monday 13:30 Go to Income distribution in Türkiye which was referenced above as Self study before. Examine the page including all its links and data tables. Your task is to prepare a report on 'how fair the income distribution in Türkiye is', i.e., whether it is fair; if not, what makes you to conclude it isn't. In that, first learn on your own the terms 'fair', 'just', 'equal' and 'equitable' referring to economics textbooks and/or AI of your choice. Your quantitative assessment must be based on what you've learned in Chapter 1, where your knowledge therein should enable you to learn new things you'll encounter, so, do your research. Once your analysis is done, prepare a research note (a short paper) of 1500 to 2000 words that includes all of the following: 'Title', 'Abstract (100-120 words)', 'Keywords', 'Introduction', 'Literature Review', 'Methodology (refer to Lecture Notes)', 'Empirical Analysis', 'Discussion and Conclusion', 'References (a max of 5)'. Your paper will not have an Appendix or Appendices, the number of footnotes can be a maximum of 5 and endnotes are not allowed. Use of AI in writing is not suggested; write your work on your own. Regarding the format of your paper (format elements: fonts, spacing; captions: enumeration and titling of visuals; layout elements: page structure and enumeration, etc.), briefly review the published empirical papers of the faculty members of your department and maintain the format of one of those published after 2020. If you are not from ECON or MAN, refer to ECON faculty's papers. Cite this guiding paper in your References. Print your report to file in PDF format. Finalize your Excel file (just one) used in analysis so that it will be self-explanatory and it will include everthing done. Your files must be named as: 221-Hw1-11111111.pdf and 221-Hw1-11111111.xlsx, where 11111111 is your ID number. Not naming your files as described will result in the rejection of your submission. Submit both files in the same email message as 'file attachments' (not 'cloud-based links') to your TA's email address with proper salutation and body text. Upon receiving your submission, your TA will send you a message including the word "Received". Grading: No submission=0 points, Late submission=15 points deduction. Other deductions will be announced by the TA team. Note that Homework performance makes up 20%of your semester total; so, sharing your work in any form with other students may harm your individual letter grade assessment. Unacceptably high similarity between submissions will yield a grade of 0 points as well as possible disciplinary investigation. Unless otherwise noted, these rules apply to all Homework assignments.
Excel (Page)
2 Probability basics
2.1 Modeling a Random Experiment
2.2 Properties of a probability measure: Probability postulates
2.3 Probability versus possibility
2.4 Methods of assigning probability
2.5 Counting
221 Handout 240219 - Exercises on Probability basics.pdf
2.6 Conditional probability
2.7 Bayes’ Theorem Bayes' Theorem not included in 221 Mt1 so expect a question in 221 Mt2
2.8 Independence of events
2.9 Bivariate probabilities
2.10 Joint, marginal and conditional probabilities
2.11 Independence of Events 221 Mt1 up to here except for Bayes' Theorem
221 Rec 5 Mt1 solutions to be covered Past materials (Folder)
221 Handout 240305 - Conditional probability - Independence of events.pdf
060 Preparing Cross Tabulations using PIVOT TABLE and calculating Conditional probabilities.xlsx 221 Rec 6
070 Describing data via PIVOT TABLEs to reveal Global warming.xlsx 221 Rec 6
SD (XLSX) z (PDF, PNG) Excel (Page)
3 Random variables
3.1 Random Variables
3.2 Cumulative distribution function: CDF
3.3 Continuous and discrete random variables
3.4 Probability distribution functions
221 Hw2 due 26 November 2025 Wednesday 13:30 Examine & think in-depth on the following questions: (1) What is randomness? In that, what do the terms 'random' and 'stochastic' stand for? Add other terms if you think it is necessary. (2) Is it possible to generate 'purely random' numbers? If no, why; if yes, how? (3) In many movies it is said "There is no such thing as a coincidence". How can you elaborate on this statement? Note that none of these is a query on your opinions; rather they require technically- and/or philosophically-based responses. Use of AI in researching is allowed; yet, blend it with your further self-reading. Once your analysis is done, prepare a research note (a short paper) of 2000-2400 words that includes a well-organized and well-written treatment of (1), (2), and (3). The components to be included are 'Title', 'Abstract (100-120 words)', 'Keywords', 'Introduction', 'Literature Review', 'Discussion' and 'Conclusion', 'References (a max of 5)'. Your paper will not have an Appendix or Appendices, the number of footnotes can be a maximum of 5 and endnotes are not allowed. Use of AI in writing is not suggested; write your work on your own. Regarding the format of your paper (format elements: fonts, spacing; captions: enumeration and titling of visuals; layout elements: page structure and enumeration, etc.), briefly review the published empirical papers of the faculty members of your department and maintain the format of one of those published after 2020. Cite this guiding paper in your References. Print your report to file in PDF format. Your file must be named as: 221-Hw2-11111111.pdf, where 11111111 is your ID number. Not naming your files as described will result in the rejection of your submission. Submit your file in an email message as a 'file attachment' (not a 'cloud-based link') to your TA's email address with proper salutation and body text. Upon receiving your submission, your TA will send you a message including the word "Received". Grading: No submission=0 points, Late submission=15 points deduction. Other deductions will be announced by the TA team. Note that Homework performance makes up 20%of your semester total; so, sharing your work in any form with other students may harm your individual letter grade assessment. Unacceptably high similarity between submissions will yield a grade of 0 points as well as possible disciplinary investigation.
3.5 Expected Value
221 Handout 240426 - Exercises on PDF - CDF - Expected value.pdf
3.6 Variance and standard deviation
3.7 Random variables and distributions: Discrete probability laws 221 is here 221 Mt2 will be up to the end of 3.7
3.8 Random variables and distributions: Continuous probability laws
221 Hw3 due DD MMM YYYY Day HH:MM Hw description
221 Handout 241217 - Approximations to Binomial - CT - LOLN - CLT.pdf
080 Generating random numbers using RAND and the Inverse Transformation Technique - 1.xlsx 222 Rec 1
090 Generating random numbers using RAND and the Inverse Transformation Technique - 2.xlsx 222 Rec 1
100 Solving a Bayes theorem question via Simulation.xlsx
110 Conditional probabilities Statistical Independence - an exercise on student performance.xlsx
120 Simulating the Geometric distribution.xlsx 221 Rec 7
130 Simulating the Negative Binomial distribution.xlsx 221 Rec 7
140 Simulating Poisson arrivals of customers via Exponential interarrival times - Inverse Transformation Technique.xlsx
150 Inverse Transformation Technique and calculating Expected Value via simulation for an interesting distribution.xlsx
160 Inverse Transformation Technique and calculating Expected Value via simulation for the Logistic distribution.xlsx
170 Inverse Transformation Technique for a semicircularly shaped distribution .xlsx
180 Simulating a Galton Board.xlsx 222 Rec 2 221 Rec 8
190 Simulating an asymmetric Galton Board.xlsx
200 Calculating Expected Value via simulation - Miner question.xlsx
210 Calculating Expected Value via simulation - an advanced exercise.xlsx
220 Estimating pandemic-epidemic probabilities for the future - an advanced exercise.xlsx
230 Poisson arrivals via Exponential interarrival times and the Law of Large Numbers theorem.xlsx 222 Rec 2
221 Hw4 due DD MMM YYYY Day HH:MM Hw description
3.9 Random variables and distributions: Moments of distributions [Optional material]
3.10 Moment generating functions [Optional material]
3.11 Random vectors [Optional material]
SD (XLSX) z (PDF, PNG) Excel (Page)
4 Sampling distributions
4.1 Chebyshev’s theorem
4.2 Law of large numbers theorem
4.3 Central limit theorem
4.4 Distribution of sample means 221 Fnl will be up to the end of 4.4
240 Sampling from a finite population using RAND-INDEX-RANK combination.xlsx 222 Rec 3
222 Hw1 due 20 October 2025 Monday 13:30 Create two towns: town A with 5000 and town B with 1000 residents (citizen, person living in town). Each town will be on a separate worksheet of the same Excel workbook. Each citizen will be represented in a row with the following attributes: incomes in town A will come from an Exponential (1/100000) and incomes in town B will come from a Normal(100000, 225000000) distribution. Each citizen in each town will support either political party X or political party Y: in town A, each citizen has an independent probability of 0.60 to vote for X; in town B, it is 0.40. In each town half of the population is women and half is men. In this Homework, there is no statistical dependence between income, political tendency and gender variables; you'll introduce these in a subsequent homework. Note that, lambda, mu, sigma-square and P (figure out which is which) must be parameters in Excel, i.e., when you change them in their designated cells, incomes, political tendencies and genders must change. While submitting your work, the given parameters must be effective on your file. Make sure you've generated the distributional graphs and a rich set of descriptive statistics: go to Chapter 1. For each distributional parameter, check and document if the experimentally obtained (empirical) parameters match the theoretical (input) ones. Use of AI is not suggested in this homework. Once your work is done, annotate your Excel file with text boxes & make all necessary explanations therein: what you did, how you did & why you did must all be crystal-clear. Your file (just one) must be named as: 222-Hw1-11111111.xlsx, where 11111111 is your ID number. Not naming your file as described will result in the rejection of your submission. Submit the file in an email message as a 'file attachment' (not a 'cloud-based link') to your TA's email address with proper salutation and body text. Upon receiving your submission, your TA will send you a message including the word "Received". Grading: No submission=0 points, Late submission=15 points deduction. Other deductions will be announced by the TA team. Note that Homework performance makes up 20%of your semester total; so, sharing your work in any form with other students may harm your individual letter grade assessment. Unacceptably high similarity between submissions will yield a grade of 0 points as well as possible disciplinary investigation. Unless otherwise noted, these rules apply to all Homework assignments.
221 Hw5 due DD MMM YYYY Day HH:MM Hw description