Statistics


Statistics

Statistics
 
Course Code BSC304
Qualification Statement of Attainment
Payment Options Upfront & Payment Plans
Delivery Online & Correspondence
Duration 100 Hours

 
Course Information

Statistics involves gathering, organising and analysis of data (normally numerical). In enables us to draw conclusions and make inferences on the basis of such analyses.

Descriptive statistics describe a set of data, while inferential statistics make inferences about large groups based on data from a smaller subset of the group. To infer means to draw a conclusion based on facts or premises. Thus an inference is the end result; a proposition based on the act of inferring.

Statistical data is critical to management of every commercial or government enterprise. Without statistics, our understanding of society, and the physical world; not to mention economics; would be greatly diminished.

There are 10 lessons in this course:

  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
    • Cooeficient of determination
    • Scatter plots
    • Product movement forlinear 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 independant samples
    • t Test for dependant (paired) samples
  9. Analysis of variance
    • Scope and application of ANOVA
    • Factors and levels
    • Hypothesis
    • Calculate degrees of freedon
    • Calculate sum of squares within and between groups
    • Calculate mean square
    • Calculate F
  10. Chi square test
    • Chi quare goodness of fit test
    • Calculate degrees of freedom
    • Chi square test of independance
    • Calculate expected frquencies
    • Degrees of freedon
    • Contingency tables
    • Find expected frequencies
    • Calculate degrees of freedom

Each lesson culminates in an assignment which is submitted to the school, marked by the school's tutors and returned to you with any relevant suggestions, comments, and if necessary, extra reading.

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.
  • Analyze 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

For more information on this course, please request your free course information pack. 

Finance options

If you are an Irish citizen you may be eligible to receive financial support, meaning you can defer payment of your course fees. Additionally, if you are a resident of Ireland, you may also be eligible to receive a student grant under the Student Grant Scheme

Student support

We live in a society where the pressures of daily living are high with financial expenses, personal and work commitments, and mortgage and rental obligations. Then there are the unexpected life challenges that also get thrown our way. With this in mind the thought of taking on study can be daunting for most people. Here at Learning Cloud we understand that life doesn’t run in a straight line it has many ups and downs.

As an enrolled student at Learning Cloud, you are entitled to access a variety of non-academic support services from the Student Services Unit. These supports are designed to walk beside you throughout your studies they will assist you in life’s ups and downs to provide you the best opportunity to successfully complete your chosen course.

STUDENT SERVICES PROGRAMS INCLUDE:

  • Careers Counselling Service
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  • Reasonable Adjustment Plan (RAP)

Call our student support today on 0419803370 or Email Faculty

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How will this course advance my career?

Learning Cloud programs have been developed in response to industry demand and are specifically designed to equip graduates with work-ready skills. Each participant will be trained and assessed in theory and in practical tasks and Real-world exercises are used throughout the program.

Studies prove, time and again, that college-educated workers earn more than those with only a high school qualification. College graduates often enjoy additional benefits, including greater job opportunities and promotions. Though the proof for greater earning potential exists, some might wonder whether the cost of the education warrants the overall expense in the long run.

College Graduate vs. Non-Graduate Earnings

The National Centre for Education Statistics (NCES) analyses employee earnings data biennially, according to education level. Findings indicate that workers with a qualification earn significantly more than those without. Since the mid-1980s, education has played a large part in potential wages, with bachelor's degree holders taking home an average of 66% more than those with only a high school diploma do. While college-educated workers' wages have increased over the past two decades, those with only a high school education have seen decreases in annual salaries in the same time period (nces.ed.gov).

How else will I benefit from studying with Learning Cloud?

  • Studying online or distance means you can study where you want and at your own pace.
  • Receive career-focused training with practical, hands-on learning.
  • All course materials are provided and all digital platforms are interactive, work on any device and designed to be fun.
  • Recognition of Prior Learning or Skills Recognition may be available for previous work experience, formal training or qualifications in this field.

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