Why Study this Statistics Course?

Do you want to gain a solid foundation in statistics? Then, this online statistics course will give you what you need! This course will teach you all the fundamental knowledge that there is in statistics. Such as how to differentiate two groups using a t-test, how to correlate two variables, how to apply measures of central tendency in research, and much more.

Statistics is an important skill for anyone involved or is interested in the measurement and prediction of trends in either markets, science, the environment, or health science.  It is one of the true tools that are cross-disciplinary.

Course Aims:

  • Become familiar with different statistical terms and the elementary representation of statistical data.
  • Become familia with distributions, and the application of distributions in processing data.
  • Apply measures of central tendency in solving research questions
  • Demonstrate and explain the normal curve, percentiles and standard scores.
  • Explain methods of correlation that describes the relationship between two variables.
  • Make predictions with regression equations.
  • Determine how much error to expect when making the predictions.
  • Explain the basic concepts of underlying the use of statistics to make inferences.
  • Analyse the difference between the means of two groups with the t Test.
  • Describe the use of ANOVA (Analysis of Variance) in analysing the difference between two or more groups.
  • Apply the concept of Non Parametric Statistics

Statistics – Online Course – Supported Learning

  • understand data in your industry
  • achieve your educational goals
  • get a career in science or maths

Duration:   100 hours

 

COURSE STRUCTURE

There are 10 lessons as follows:

1. Introduction
  • Key terms and concepts: data, variables
  • Measurements of scale: nominal, ordinal, interval,ratio
  • Data presentation
  • Probability
  • Rounding of data
  • Scientific notation
  • Significant figures
  • Functions
  • Equations
  • Inequalities
  • Experimental design
  • The normal curve
  • Data collection
  • Simple, systemic, stratified and cluster random sampling
  • Remaining motivated to learn statistics
2. Distributions
  • Scope and nature of distributions
  • Class intervals and limits
  • Class boundaries
  • Frequency Distribution
  • Histograms
  • Frequency polygons
  • Normal distributions
  • Other distributions
  • Frequency curves
3. Measures of central tendency
  • Range, percentiles, quartiles, mode, median, mean
  • Variance
  • Standard deviation
  • Degrees of freedom
  • Interquartile and semi interquartile deviations
4. The Normal curve and Percentiles and Standard Scores
  • Normal distribution characteristics
  • Percentiles
  • Standard scores
  • Z scores
  • T score
  • Converting standard scores to percentiles
  • Area under a curve
  • Tables of normal distribution
5. Correlation
  • Scope and nature of Correlation
  • Correlation coefficient
  • Coefficient of determination
  • Scatter plots
  • Product movement for linear correlation coefficient
  • Rank correlation
  • Multiple correlation
6. Regression
  • Calculating regression equation with correlation coefficient
  • Least squares method
  • Standard error of the estimate
7. Inferential Statistics
  • Hypothesis testing
  • Test for a mean
  • Errors in accepting or rejecting null hypothesis
  • Levels of significance
  • One and two tailed tests
  • Sampling theory
  • Confidence intervals
8. The t Test
  • Assessing statistical difference with the t test
  • t Test for independent samples
  • t Test for dependent (paired) samples
9. Analysis of variance
  • Scope and application of ANOVA
  • Factors and levels
  • Hypothesis
  • Calculate degrees of freedom
  • Calculate sum of squares within and between groups
  • Calculate mean square
  • Calculate F
10. Chi square test
  • Chi square goodness of fit test
  • Calculate degrees of freedom
  • Chi square test of independence
  • Calculate expected frequencies
  • Degrees of freedom
  • Contingency tables
  • Find expected frequencies
  • Calculate degrees of freedom

 

Enrol Now

  • Experienced Tutor support
  • Certificate sent to you
  • Online study (Printed notes available)
  • Self paced - no set timetable
  • 12 months to complete course

$599.00

Send me a free info pack

    CourseStream Accreditation.
    Accredited courses.

     

    Enrol Now

    • Experienced Tutor support
    • Certificate sent to you
    • Online study (Printed notes available)
    • Self paced - no set timetable
    • 12 months to complete course

    $599.00

    Send me a free info pack

      CourseStream Accreditation.
      Accredited courses.
      GET YOUR FREE INFO PACK

       

      Why Study this Statistics Course?

      Do you want to gain a solid foundation in statistics? Then, this online statistics course will give you what you need! This course will teach you all the fundamental knowledge that there is in statistics. Such as how to differentiate two groups using a t-test, how to correlate two variables, how to apply measures of central tendency in research, and much more.

      Statistics is an important skill for anyone involved or is interested in the measurement and prediction of trends in either markets, science, the environment, or health science.  It is one of the true tools that are cross-disciplinary.

      Course Aims:

      • Become familiar with different statistical terms and the elementary representation of statistical data.
      • Become familia with distributions, and the application of distributions in processing data.
      • Apply measures of central tendency in solving research questions
      • Demonstrate and explain the normal curve, percentiles and standard scores.
      • Explain methods of correlation that describes the relationship between two variables.
      • Make predictions with regression equations.
      • Determine how much error to expect when making the predictions.
      • Explain the basic concepts of underlying the use of statistics to make inferences.
      • Analyse the difference between the means of two groups with the t Test.
      • Describe the use of ANOVA (Analysis of Variance) in analysing the difference between two or more groups.
      • Apply the concept of Non Parametric Statistics

      Statistics – Online Course – Supported Learning

      • understand data in your industry
      • achieve your educational goals
      • get a career in science or maths

      Duration:   100 hours

       

      COURSE STRUCTURE

      There are 10 lessons as follows:

      1. Introduction
      • Key terms and concepts: data, variables
      • Measurements of scale: nominal, ordinal, interval,ratio
      • Data presentation
      • Probability
      • Rounding of data
      • Scientific notation
      • Significant figures
      • Functions
      • Equations
      • Inequalities
      • Experimental design
      • The normal curve
      • Data collection
      • Simple, systemic, stratified and cluster random sampling
      • Remaining motivated to learn statistics
      2. Distributions
      • Scope and nature of distributions
      • Class intervals and limits
      • Class boundaries
      • Frequency Distribution
      • Histograms
      • Frequency polygons
      • Normal distributions
      • Other distributions
      • Frequency curves
      3. Measures of central tendency
      • Range, percentiles, quartiles, mode, median, mean
      • Variance
      • Standard deviation
      • Degrees of freedom
      • Interquartile and semi interquartile deviations
      4. The Normal curve and Percentiles and Standard Scores
      • Normal distribution characteristics
      • Percentiles
      • Standard scores
      • Z scores
      • T score
      • Converting standard scores to percentiles
      • Area under a curve
      • Tables of normal distribution
      5. Correlation
      • Scope and nature of Correlation
      • Correlation coefficient
      • Coefficient of determination
      • Scatter plots
      • Product movement for linear correlation coefficient
      • Rank correlation
      • Multiple correlation
      6. Regression
      • Calculating regression equation with correlation coefficient
      • Least squares method
      • Standard error of the estimate
      7. Inferential Statistics
      • Hypothesis testing
      • Test for a mean
      • Errors in accepting or rejecting null hypothesis
      • Levels of significance
      • One and two tailed tests
      • Sampling theory
      • Confidence intervals
      8. The t Test
      • Assessing statistical difference with the t test
      • t Test for independent samples
      • t Test for dependent (paired) samples
      9. Analysis of variance
      • Scope and application of ANOVA
      • Factors and levels
      • Hypothesis
      • Calculate degrees of freedom
      • Calculate sum of squares within and between groups
      • Calculate mean square
      • Calculate F
      10. Chi square test
      • Chi square goodness of fit test
      • Calculate degrees of freedom
      • Chi square test of independence
      • Calculate expected frequencies
      • Degrees of freedom
      • Contingency tables
      • Find expected frequencies
      • Calculate degrees of freedom

       

      Enrol Now

      • Experienced Tutor support
      • Certificate sent to you
      • Online study (Printed notes available)
      • Self paced - no set timetable
      • 12 months to complete course

      $599.00

       

      Get a Free Info Pack!

        CourseStream Accreditation.
        Accredited courses.