Jargon for Statistics I.
BEFORE MIDTERM
Descriptive versus inferential statistics,
Population, sample, data frame,
Statistic, parameter, Positive Skewness, Negative Skewness.
Time series data, cross-sectional data, non-stationary series
Interval data, ratio data, levels of measurement,
Nominal data, ordinal data, relative frequency,
Placebo Effect, Simpson's paradox,
Requirements for a good graph (source, heading, axes labels, scale, legend, etc.), box and whisker plot, Pareto plot
quantitative and qualitative data.
Frequency distribution, probability distribution,
Outlier, measures of dispersion (variance, standard deviation,
Range, IQR, etc) Empirical Rule, Z-score, two-sigma Rule.
MAD (mean absolute deviation)
Measures of central tendency (mean, median, mode),
Weighted Average and examples (Dow Jones Industrial, S&P 500, Consumer Price Index)
Percentile, coefficient of variation. Moving average.
Stratified random sample.
Here a typical question will be:
Population has 25 students of whom 15 are white and 10 black. A stratified sample of size 10 should have how many whites / blacks?
Answer: Let N=population size, N1=blacks=10, N2=whites =15, n=sample size=10. Note that N1 /N =(10/25)*10 or 4 blacks and
How many whites in the sample? (N2/N)*n= (15/25)*10 or 6
Verify that 6+4=10. We aim to have a representative sample
In the following frequency table insert two dummy intervals, plot
the two ogives and find the median graphically.
Lower Upper freq
20—----50, 2
50—----80 9
80—----110 6
AFTER MIDTERM
FINAL exam Part I will be during the class on Monday, Dec. 10,
as a webtest on the computer software
Part I of the Final Exam is set at 30% of your grade
will focus on the following lessons from the Hawkeslearning computer software
4.3 Counting Rules
4.4 Additional counting rules
5.1 Discrete Random Variable
5.2, Binomial
5.3, Poisson
5.4, hypergeometric
6.2 Reading the Normal curve Table
6.3, normal distribution word problems
6.4, find z
7.2 sampling distribution proportions
7.3, sampling dist means
7.4 Approximating the Binomial Dist using the Normal Distribution
Jargon Items for Part 2 of the Final Exam, set at 10% of your grade
Sampling distribution (size of the sample space when n items are chosen for a sample from a population of N items
answer= N C n, enumerate these if N and n are small)
Expected value of a random variable. Sharpe Ratio
In what sense is it irrational to do Casino gambling?
[Hint: check information in textbook on expected value, note that expected value is negative for gambling]
Statistical independence
[Hint: check contingency tables discussion where it says that independence means unconditional probability equals the conditional probability]
Conditional probability,
Marginal probability, compound event, simple event,
Examples of discrete random variables and
continuous random variables.
Uniform random variable.
Simple random sample.
Bayes Theorem Statement.
Definitions: Posterior probability, Prior Probability, Likelihood function
Central Limit Theorem.
Standard Normal Variable (=z)
Sampling Frame.
FPC = Finite population correction = (N-n)/(N-1)
Correction for continuity (Check textbook under continuity correction)