Data Research Statistical Approaches

Data Research    |    Intermediate
  • 13 videos | 42m 49s
  • Includes Assessment
  • Earns a Badge
Rating 3.3 of 14 users Rating 3.3 of 14 users (14)
This 12-video course explores implementation of statistical data research algorithms using R to generate random numbers from standard distribution, and visualizations using R to graphically represent the outcome of data research. You will learn to apply statistical algorithms like PDF (probability density function), CDF (cumulative distribution function), binomial distribution, and interval estimation for data research. Learners become able to identify the relevance of discrete versus continuous distribution in simplifying data research. This course then demonstrates how to plot visualizations by using R to graphically predict the outcomes of data research. Next, learn to use interval estimation to derive an estimate for an unknown population parameter, and learn to implement point and interval estimation by using R. Learn data integration techniques to aggregate data from different administrative sources. Finally, you will learn to use Python libraries to create histograms, scatter, and box plot; and use Python to implement missing values and outliers. The concluding exercise involves loading data in R, generating a scatter chart, and deleting points outside the limit of x vector and y vector.

WHAT YOU WILL LEARN

  • Describe the features provided by statistical methods and approaches in data research
    Identify the relevance of discrete vs continuous distribution in simplifying data research
    Recognize the features of pdf and cdf from the perspective of data research
    Implement binomial distribution using r
    Specify the types of interval estimation that can be used to enhance data research
    Implement point and interval estimation using r
  • Describe the relevance of data visualization techniques in projecting the outcome of data research
    Plot visualizations using r to depict the outcome of data research graphically
    Recall the data integration techniques that facilitate using statistical methods
    Create histograms, scatter plots, and box plots using python libraries
    Implement missing values and outliers using python
    Implement data research using various statistical approaches

IN THIS COURSE

  • 1m 52s
  • 3m 33s
    Upon completion of this video, you will be able to describe the features provided by statistical methods and approaches to data research. FREE ACCESS
  • Locked
    3.  Discrete vs. Continuous Distribution
    3m 16s
    In this video, learn how to identify the relevance of discrete or continuous distribution in simplifying data research. FREE ACCESS
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    4.  PDF and CDF
    6m 33s
    After completing this video, you will be able to recognize the features of PDFs and CDFs from the perspective of data research. FREE ACCESS
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    5.  Binomial Distribution
    3m 16s
    In this video, you will learn how to implement binomial distribution using R. FREE ACCESS
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    6.  Interval Estimation
    3m 16s
    Upon completion of this video, you will be able to specify the types of interval estimation that can enhance data research. FREE ACCESS
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    7.  Point and Interval Estimation
    3m 35s
    In this video, you will learn how to use point and interval estimation using R. FREE ACCESS
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    8.  Data Visualization Techniques
    2m 11s
    After completing this video, you will be able to describe the relevance of data visualization techniques in data research outcomes. FREE ACCESS
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    9.  Data Visualization Using R
    2m 39s
    In this video, you will plot visualizations using R to depict the outcome of your data research graphically. FREE ACCESS
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    10.  Data Integration Techniques
    3m 11s
    After completing this video, you will be able to recall the data integration techniques that facilitate using statistical methods. FREE ACCESS
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    11.  Creating Plots
    3m 59s
    During this video, you will learn how to create histograms, scatter plots, and box plots using Python libraries. FREE ACCESS
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    12.  Missing Values and Outliers
    3m 5s
    In this video, learn how to deal with missing values and outliers using Python. FREE ACCESS
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    13.  Exercise: Statistical Methods for Data Research
    2m 23s
    Find out how to implement data research using various statistical approaches. FREE ACCESS

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