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(MATH 2785) Business Statistics First Exam Prep
Statistics giving you a hard time? Chill out with this complete guide of Lecture 1-7 . I'll help you out with easy-to-understand and step-by-step examples of the main concepts.
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Summary Lecture 7-8
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summary; and brief, clear, and easy-to-understand examples of main concepts: Calculating probability, intersection of events, union of events, addition rule, conditional probability, multiplication rule, independent or dependent events
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Summary Lecture 6
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summary; and brief, clear, and easy-to-understand examples main concepts: Calculating Classical Probability, Empirical Probability, Complement, and rules of probabilities.
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: Calculating Classical Probability, Empirical Probability, Complement, and rules of probabilities.
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Summary Lecture 5
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summary; and brief, clear, and easy-to-understand examples main concepts: Computing Percentiles, five number summary, interquartile range, limits and Box-and-Whisker Plot
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: Computing Percentiles, five number summary, interquartile range, limits and Box-and-Whisker Plot
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Summary Lecture 4
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summary; and brief, clear, and easy-to-understand examples main concepts: Calculating Sample/population Variance, standard deviation, z-score, distribution if bell-shaped, grouped data.
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: Calculating Sample/population Variance, standard deviation, z-score, distribution if bell-shaped, grouped data.
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Summary Lecture 3
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summary; and brief, clear, and easy-to-understand examples main concepts: Calculating mean, median, mode, weighted mean, pros and cos, distribution, skewed...
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: Calculating mean, median, mode, weighted mean, pros and cos, distribution, skewed...
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Summary Lecture 2
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summary; and brief, clear, and easy-to-understand examples main concepts: Variables, Relative Frequency, Quantitative data, percentage, number of classes, class width, cumulative frequency, cumulative relative frequency, discrete data, continuous data, histogram...
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: Variables, Relative Frequency, Quantitative data, percentage, number of classes, class width, cumulative frequency, cumulative relative frequency, discrete data, continuous data, histogram...
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Summary Lecture 1
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summary; and brief, clear, and easy-to-understand examples main concepts: statistics, data, qualitative data, quantitative data, descriptive statistics, inferential statistics, population, sample, parameter,
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Add to cartsummary; and brief, clear, and easy-to-understand examples main concepts: statistics, data, qualitative data, quantitative data, descriptive statistics, inferential statistics, population, sample, parameter,
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