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Official Course
Description: MCCCD Approval: 4-24-2007 |
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GBS221 2007 Fall – 2011 Summer II |
LEC 3.0 Credit(s) 3.0 Period(s) 3.0 Load Acad |
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Business
Statistics |
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Business applications of descriptive and inferential statistics,
measurement of relationships, and statistical process management. Includes
the use of spreadsheet software for business statistical analysis. Prerequisites: Grade of C or better in
GBS220 or MAT217. Course
Attribute(s): General
Education Designation: Computer/Statistics/Quantitative Applications - [CS] |
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Go to Competencies Go to Outline
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MCCCD
Official Course Competencies: |
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GBS221 2007
Fall – 2011 Summer II |
Business Statistics |
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1.
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Collect, organize, present, analyze, and interpret
numerical data using frequency distributions and graphical presentations. (I)
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2.
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Calculate and interpret the measures of central tendency for
either raw or grouped data. (I) |
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3.
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Calculate and interpret the measures of dispersion and skewness for a data set. (I) |
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4.
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Use discrete and continuous probability distributions in
probability applications. (II) |
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5.
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Explain probability sampling and sampling distributions,
and describe their uses. (III) |
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6.
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Use statistical inference techniques and confidence levels
for decision making when testing hypotheses. (IV) |
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7.
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Use regression and correlation analysis, and interpret the
results of the analysis. (V) |
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8.
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Use statistical process management and control charting to
solve statistical quality control problems. (VI) |
Go to Description Go to top of
Competencies
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MCCCD
Official Course Outline: |
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GBS221 2007
Fall – 2011 Summer II |
Business Statistics |
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I. Collection,
Organization, Presentation, Analysis, and Interpretation of Numerical Data A. Frequency Distribution B. Graphical Representation
1. Histogram 2. Frequency Polygon C. Measures of Central
Tendency (Ungrouped and Grouped) 1. Mean 2. Median 3. Mode D. Measures of Dispersion
(Ungrouped and Grouped) 1. Range 2. Variance 3. Average Deviation 4. Standard Deviation 5. Empirical Rule 6. Skewness
7. Relative Dispersion II. Probability, Counting
Methods, and Probability Distributions A. Rules of Multiplication
and Addition B. Bayes Theorem C. Combinations and
Permutations D. Random Variables E. Discrete Random
Variables F. The Binomial
Distribution G. Poisson Distribution H. The Normal Probability
Distribution III. Sampling Methods and
Sampling Distribution A. Probability Sampling B. Sampling Error C. Sampling Distribution of
the Means D. Central Limit Theorem E. Confidence Intervals F. Selecting a Sample Size 1. Mean 2. Proportion IV. Hypothesis Testing A. Large Samples 1. Means a. Testing One Population
Mean b. Testing the Difference Between
Two Population Means 2. Proportions a. Testing One Population
Proportion b. Testing the Difference
Between Two Population Proportion B. Small Samples 1. Testing One Population
Mean 2. Comparing Two Population
Means V. Regression and Correlation
A. Coefficients of
Correlation and Determination B. Testing the Significance
of the Coefficient of Correlation C. Regression Equation D. Standard Error of the
Estimate E. Confidence-Interval
Estimates VI. Statistical Quality
Control A. The Control Chart B. Acceptance Sampling |