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Analyze the importance of statistics in everyday life
Assessment Strategies
In-class assignment
Criteria
Evaluate use of statistics in everyday life
Analyze the importance of statistics in the social sciences and the furthering of scientific knowledge
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Employ appropriate language in describing research data
Assessment Strategies
In-class assignment and semester project
Criteria
Investigate levels of measurement and levels and association
Differentiate between population and sample data
Differentiate between qualitative and quantitative data
Explain theories of sampling
Compare descriptive statistics and inferential statistics
Identify different methods for collecting data and their appropriate use
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Analyze data using calculator and appropriate software when available
Assessment Strategies
Homework and semester project
Criteria
Calculate solutions to exercises
Distinguish between variables and cases
Define new variables with appropriate labels and codes
Label new variables according to level of measurement
Code data and enter data according to variable definitions
Save data file and send data file electronically
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Employ appropriate representations of sample data
Assessment Strategies
In-class assignment and/or homework
Criteria
Generate a frequency list, by hand, showing both relative frequencies and cumulative frequencies from a given data set
Use software to generate a frequency list showing both relative frequencies and cumulative frequencies from a given data set
Construct a table, bar chart, histogram, and scatter plot using frequency list
Determine appropriate representation of data given type of data and the use of representation
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Calculate measures of central tendency
Assessment Strategies
In-class assignment, homework, quiz and/or exam
Criteria
Calculate the mean of a series of data points
Calculate the median of a series of data points
Calculate the mode of a series of data points
Demonstrate the successful use of software to calculate central tendencies
Use mean, median, and mode given a set of data points
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Calculate measures of dispersion
Assessment Strategies
In-class assignment, homework, quiz and/or exam
Criteria
Calculate the range and interquartile range of a series of data points
Calculate the standard deviation and variance of a series of data points
Differentiate between population and sample measures of dispersion
Demonstrate the successful use of software to calculate measures of dispersion
Demonstrate application of measures of dispersion
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Calculate and compare distributions
Assessment Strategies
In-class assignment, homework, quiz and/or exam
Criteria
Demonstrate the concept of the Normal Curve
Calculate Z scores
Interpret Z score distributions appropriately and accurately
Compare and contrast distributions in respect to central tendencies
Compare and contrast distributions in respect to dispersions
Interpret differences of distributions in practical problems in the social sciences
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Recode data and create composite variables
Assessment Strategies
In-class assignment and homework
Criteria
Recode variables
Compare and contrast recoded variables with original variables
Determine when and why to recode variables
Construct composite variables
Compare and contrast composite variables with original variables
Determine when and why to construct composite variables
Interpret the application of recoded and composite variables in practical problems in the social sciences
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Calculate probability, estimation, and differentiate inferential statistics
Assessment Strategies
In-class assignment, homework, quiz and/or exam
Criteria
Explain the purpose behind inferential statistics in regards to generalizing from the sample to the population
Demonstrate randomized sampling and sampling techniques
Define and identify sampling key terms such as population, sampling, parameter, statistic, probability sampling, and standard error of the mean
Demonstrate two theorems involved in the sampling process
Define sampling distribution and its characteristics
Show competence in communicating various statistical symbols for distribution characteristics, such as sample mean, population mean, sample standard deviation, and population standard deviation
Demonstrate understanding of estimation
Calculate confidence intervals for sample means and for sample proportions
Interpret the application of confidence intervals and estimation in social science problems
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Test hypotheses
Assessment Strategies
In-class assignment, homework, quiz, and/or exam
Criteria
Explain the logic of hypothesis testing
Apply key terms, such as null hypothesis, alpha level and test statistic
Describe how and why one would “reject the null hypothesis”
Describe the differences between one-tailed and two-tailed tests and when to apply one over the other
Differentiate between Type I and Type II errors
Test, through calculation, significance of one sample case in terms of means and proportions in both small and large sample sizes
Test, through calculation, significance of two sample case in terms of means and proportions in both small and large sample sizes
Test, through calculation, hypotheses using analysis of variance and chi square
Apply key concepts, such as population variance, various sum of square concepts, and the difference between statistical significance and importance
Interpret the application of ANOVA and Chi Square in social science problems
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Determine the factors of bivariate association and measures of association
Assessment Strategies
In-class assignment, homework, quiz, and/or exam
Criteria
Use measures of association to describe and analyze importance of relationships compared to their statistical significance
Demonstrate purpose of bivariate tables in terms of defining associations between variables and distributions
Describe association in terms of existence, strength, and pattern or direction
Calculate percentages for a bivariate table and interpret results
Use software to compute measures of association and successfully interpret results.
Calculate Phi, Cramer’s V, and Lambda by hand and through SPSS
Identify the proportional reduction in error
Demonstrate measures of association at nominal, ordinal, and interval-ratio levels of analysis
Calculate Gamma and Spearman’s Rho
Interpret a scattergram in terms of a bivariate relationship
Calculate and interpret slope, Y intercept, and Pearson’s r and Pearson’s r2
Calculate least-squares regression line and be able to use it to predict values of Y
Demonstrate total, explained, and unexplained variance in terms of bivariate relationship at interval-ratio level
Use software to calculate and interpret measures of association at interval-ratio level
Use software to calculate correlation matrix and successfully interpret results
Demonstrate bivariate measures of association as applied to social science problems
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Correlate Variables in Multiple Regression
Assessment Strategies
In-class assignment, homework, quiz and/or exam
Criteria
Calculate and interpret partial correlation coefficients
Calculate the least-squares multiple regression equation with partial slopes and be able to interpret results
Calculate multiple correlation coefficient and interpret results
Differentiate between direct, spurious, and intervening relationships within multiple regression models
Predict Y values within multiple regression model
Demonstrate multivariate measures of association as applied to social science problems
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Construct survey, complete analysis, and report results
Assessment Strategies
Survey, data collection with survey instrument, data analysis and written interpretation
Criteria
Construct a ten-item survey instrument focusing on topic given in class
Survey at least twenty respondents
Code survey instrument
Define survey variables into software or spreadsheet and enter data from completed surveys
Complete frequency distributions for variables, bivariate analysis, and construct a composite variable
Write an interpretation of results, including purpose of survey, proposed hypotheses, questions for future research, and provide at least one graphic display of results