Data Analysis with Microsoft Excel (Basic to Advance)
 This course is designed for individuals seeking to harness the power of Microsoft Excel for data analysis and decision-making. Participants will delve into essential Excel functions, tools, and techniques to manipulate, visualize, and analyze data effectively. From basic data cleaning to advanced statistical analysis, this course provides a comprehensive guide to unlocking the full potential of Excel for data-driven insights.
Module 1. Introduction
Module 2. Foundational Concepts of Data Analysis
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3Calculate mean and median values
Calculate mean and median values
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4Analyze data using variance and standard deviation
Analyze data using variance and standard deviation
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5Introducing the central limit theorem
Introducing the central limit theorem
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6Analyze a population using data samples
Analyze a population using data samples
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7Identify and minimize sources of error
Identify and minimize sources of error
Module 3. Visualize Data
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8Group data using histograms
Group data using histograms
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9Identify relationships using XY scatter charts
Identify relationships using XY scatter charts
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10Visualize data using logarithmic scales
Visualize data using logarithmic scales
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11Add trendlines to charts
Add trendlines to charts
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12Forecast future results
Forecast future results
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13Calculate running averages
Calculate running averages
Module 4. Test a Hypothesis
Module 5. Utilize Data Distributions
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17Use the normal distribution
Use the normal distribution
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18Use the exponential distribution
Use the exponential distribution
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19Use a uniform distribution
Use a uniform distribution
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20Use the binomial distribution
Use the binomial distribution
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21Use the poisson distribution
Use the binomial distribution
Module 6. Measure Covariance and Correlation
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22Visualize what covariance means
Visualize what covariance means
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23Calculate covariance between two columns of data
Calculate covariance between two columns of data
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24Calculate covariance among multiple pairs of columns
Calculate covariance among multiple pairs of columns
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25Visualize what correlation means
Visualize what correlation means
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26Calculate correlation between two columns of data
Calculate correlation between two columns of data
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27Calculate correlation among multiple pairs of columns
Calculate correlation among multiple pairs of columns
Module 7. Perform Bayesian Analysis
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28Introduce Bayesian analysis
Introduce Bayesian analysis
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29Analyze a sample problem: Kahneman’s Cabs
Analyze a sample problem: Kahneman’s Cabs
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30Create a classification matrix
Create a classification matrix
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31Calculate Bayesian probabilities in Excel
Calculate Bayesian probabilities in Excel
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32Update your Bayesian analysis
Update your Bayesian analysis