qnt561 | Graduate

Applied Business Research & Statistics

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This course prepares students to apply statistics and probability concepts to business decisions. Students learn important criterion for developing effective research questions, including the creation of appropriate sampling populations and instruments. Other topics include: descriptive statistics, probability concepts, confidence intervals, sampling designs, data collection, and data analysis--including parametric and nonparametric tests of hypothesis and regression analysis.

This graduate-level course is 6 weeks This course is available to take individually or To enroll, speak with an Enrollment Representative.

Course details:

Credits: 3
Duration: 6 weeks

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    Probability Distributions

    • Create and analyze binomial and Poisson discrete probability distributions, and evaluate how one can make managerial decisions.
    • Analyze normal distributions and evaluate how they are used for making managerial decisions.
    • Understand probability distribution.
    • Understand random variables and its types: discrete vs.continuous.
    • Create probability distributions and apply the concepts of mean and standard deviation of probability distributions to managerial decisions and evaluate the results.

    Sampling Distributions and Confidence Intervals

    • Apply the Central Limit Theorem and analyze how sampling distributions for sample means are used to make managerial decisions.
    • Contrast normal distributions with sampling distributions.
    • Create confidence intervals, analyze how to estimate mean and proportion, and evaluate how the estimates can be used to make management decisions.
    • Estimate sample size necessary to accomplish the purpose of study.

    Decision-Making using One-Sample Hypothesis Testing

    • Create one- and two-tailed statistical hypotheses for one-sample data.
    • Analyze Type I and Type II errors and evaluate the choice of significance levels.
    • Apply the p-value method to make rejection/non-rejection decisions for evaluating the claims about means, proportions, and standard deviations.

    Decision-Making Using Two-Sample Hypothesis Testing and ANOVA

    • Create one- and two-tailed statistical hypotheses for two-sample independent and dependent sample data.
    • Apply the p-value method to make rejection/non-rejection decisions for evaluating the claims about difference of means, proportions, and variances.
    • Understand the difference between response variables, independent variables, and treatments.
    • Apply One-Way Analysis of Variance (ANOVA) for managerial decisions in marketing, finance, and human resources.
    • Apply Two-Way Analysis of Variance (ANOVA) for making managerial decisions in marketing, finance, and human resources.

    Descriptive Statistics and Managerial Decision-Making

    • Understand what statistics is and how it is useful for making managerial decisions.
    • Understand the key statistical concepts: population vs. sample, descriptive vs. inferential statistics, parameter vs. statistic, variables, levels of measurement, and qualitative vs. quantitative data.
    • Analyze various measures of central tendency: mean, median, and mode.
    • Analyze measures of variation: range, variance, standard deviation, and coefficient of variation.
    • Evaluate skewness of a distribution.
    • Analyze percentiles, quartiles, and the Five-Number Summary.
    • Describe what probability is and when one would use it.
    • Evaluate probabilities using relative frequency approach.

    Regression and Statistical Quality Control

    • Explain regression analysis.
    • Use Excel® to create simple linear and multiple regression models, interpret the Excel® outputs, analyze the coefficient of determination to assess model’s strength and validity, and analyze the models to make predictions.
    • Explain the meaning of quality in business.
    • Create R, x ̅, p, and c control charts. Analyze and measure variation among manufactured items using control charts.
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