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STA 2215 – Elementary Statistics for Social Science
Instructor: Balázs Patkós
Email: patkosb@gmail.com
Office hours: following class or by appointment.
Textbook
Anderson, Sweeney, Williams, Freeman, and Shoesmith. 2009. Statistics for Business and
Economics. South-Western Cengage Learning. ISBN: 978-1-84480-313-2
Grading
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Homework – 25%
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Midterm – 25%
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Final exam – 40%
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Class participation – 10%
Final letter grades will be based on the McDaniel College scale in the Guidance Bulletin.
Honor code
You are expected to adhere to the McDaniel College academic honor code. Any violation will result in a zero on the related assignment or exam or other appropriate measures.
Class attendance
Class attendance is mandatory. You will be allowed two unexcused absences. Each additional absence will result in 5% reduction of the final grade.
Homework policies
Homework assignments will be distributed during the first class of the week. They must be turned in at the beginning of the first class the following week.
The final homework grade will be the average of all assignment grades, excluding the lowest.
Group work is allowed on homework assignments, but be sure that you are able to solve each problem on your own!
Software
Some homework assignments will require the use of Excel or Open Office Calc, which is available for free at http://www.openoffice.org.
Dates
Week 8: Review and midterm exam
Week 15: Final review
Topics
Basic statistics [Chapter 1-3]
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Types of data
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Scales of measurement: nominal, ordinal, interval, ratio
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Population vs. sample
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Frequency distribution and relative frequency
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Graphs, charts, histograms
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Cross-tabulations
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Measuring location: mean, median, and mode
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Measuring variability: range, variance, standard deviation, skewness
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Measuring association between two variables: covariance and correlation coefficient
Probability [Chapter 4.1-4, 5.1-5, 6.1-3 ]
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Counting rules for combinations and permutations
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Assigning probabilities
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Tree diagrams and Venn diagrams
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Complement, union, intersection, mutually exclusive events
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Conditional probability and independent events
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Discrete and continuous random variables
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Expected value and variance
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Discrete probability distributions
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Continuous probability distributions
Statistical inference [Chapter 7.1-5; 8.1-3; 9.1-4; 10.1-3; 11.1-2; 12.1-3]
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Simple random sample compared to other types of sampling
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Properties of sampling distributions
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Central limit theorem
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Margins of error and confidence intervals
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Calculating interval estimates for population mean
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Determining the sample size for a given margin of error
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Hypothesis testing
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Differences between two population means
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Tests of goodness of fit and independence
Simple linear regression [Chapter 14]
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Independent and dependent variables
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Regression model and equation
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Least squared method
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Sums of squares
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Coefficient of determination
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Assumptions about error terms
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Residual plots
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Autocorrelation
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Outliers and influential observations
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