Introductory Statistics
- Sciences
- 100 level
- 2 credit units
- 155 pages
- 20 units
This course introduces students to the basic principles and applications of statistics. It is designed for students with no prior knowledge of statistics, initiating them to the subject at an introductory stage. The course covers data collection, compilation, analysis, and presentation, along with drawing conclusions from statistical analysis. It also uses practical examples from the local environment and case studies in the social and health sectors.
About this course
- Difficulty
- Beginner
- Study hours
- 91 hours
- Maths
- Intermediate
- Content
- Theoretical, case study
- Practical work
- No
- Tutor Mark Assignments
- Final Examination
What you'll read
The real module and unit structure of STT102, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
STT102 · UNIT 1: AIMS OF THE STATISTICAL METHOD
Module Introduction Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from research data and provides different ways to assess the robustness of research outputs.
What you should be able to do
- Collect reliable statistical information
- Present data in understandable forms
- Organize and summarize collected information
- Analyze data scientifically
- Deduce meaningful conclusions from statistical analysis
What it prepares you for
- Nurse
- Medical Researcher
- Health Administrator
- Public Health Officer
- Data Analyst
- Healthcare
- Public Health
- Research
- Government
- Pharmaceuticals
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 3: Probability Distribution
Unit 4: Normal Distribution
Normal distribution concepts require strong understanding of calculus and statistical inference.
- Module 4: Hypothesis Test
Unit 2: Fundamentals of Hypothesis Test
Requires understanding of statistical inference and potential errors.
A suggested way through it
13 weeks, about 147 hours in total. Yours will differ.
- Week 1Module 1: Statistical Method
Unit 1: Aims of the Statistical Method · 7 hours
Understand the aims of statistical techniques in nursing education and practice.. Define and employ basic statistical terms..
Unit 2: Collection of Data: Sampling · 7 hours
Plan and conduct a statistical study involving health issues.. Employ an adequate or reliable method of sampling in your statistical study..
- Week 2Module 1: Statistical Method
Unit 3: Collection of Data: Bias · 7 hours
Identify bias in any statistical survey.. Recognizes sources of bias in a statistical survey..
Unit 4: Collection of Data: Forms of Record · 7 hours
Construct forms of record for collection of data.. Identify and present unambiguous questions in a form of record for collection of data..
- Week 3Module 1: Statistical Method
Unit 5: Presentation of Data · 7 hours
Tabulate and organize raw data.. Present data by means of tables, diagrams, charts and graphs..
- Week 4Module 2: Measure of Location and Dispersion
Unit 1: Frequency Distribution · 7 hours
Define frequency distribution and relative frequency.. Construct absolute and relative frequency tables..
Unit 2: Cumulative Distribution · 7 hours
Define cumulative frequency and relative cumulative frequency.. Construct cumulative frequency and relative cumulative frequency tables for a set of raw data..
- Week 5Module 2: Measure of Location and Dispersion
Unit 3: Measures of Location · 7 hours
Understand and use the summation operator in computation.. Define and compute the mean, median and mode..
Unit 4: Measure of Dispersion · 7 hours
Define and compute the range, variance and standard deviation.. Select suitable descriptive measure for summarizing data by means of percent's, percentiles..
- Week 6Module 2: Measure of Location and Dispersion
Unit 5: Correlation · 7 hours
Recognize linear and curvilinear relationships.. Display a set of data by means of scatter diagram..
- Week 7Module 3: Probability Distribution
Unit 1: Regression · 7 hours
Describe in words the use of regression analysis.. Discuss precautions in the use of regression..
Unit 2: Simple Concepts of Probability · 7 hours
Define terms relating to probability.. Identify events..
- Week 8Module 3: Probability Distribution
Unit 3: Relationship between Population and Sample · 7 hours
Define population and sample and state the relationship between them.. Describe the relationship between parameters and statistics and give examples of each..
Unit 4: Normal Distribution · 7 hours
List the properties of the normal distribution.. State the standard probabilities associated with the normal curve..
- Week 9Module 3: Probability Distribution
Unit 5: Sampling Distribution of the Mean and the Central Limit Theorem · 7 hours
Describe in words the meaning of sampling error.. Explain concisely the meaning of a derived distribution..
- Week 10Module 4: Hypothesis Test
Unit 1: Mean Estimation · 7 hours
Calculate and interpret confidence intervals on a single population mean.. Calculate and interpret confidence intervals on the difference in two population means..
Unit 2: Fundamentals of Hypothesis Test · 7 hours
List the elements of a statistical test and describe in words what is meant by null hypothesis, test statistics, level of significance, rejection region, and decision or conclusion.. Recognize these elements in a given research situation..
- Week 11Module 4: Hypothesis Test
Unit 3: Hypothesis Test for one Population Mean when Standard Deviation is Known · 7 hours
Carry out a test of hypothesis for a population mean given the standard deviation of the population..
Unit 4: Classical Approach vs P-Value Approach to Hypothesis Testing · 7 hours
Apply the p-value approach to hypothesis testing.. Interpret the results of a hypothesis test suitably..
- Week 12Module 4: Hypothesis Test
Unit 5: Measures of Morbidity · 7 hours
Recognize the need for morbidity statistics.. Identify measures of morbidity..
- Week 13Final Revision
Final Revision · 7 hours
Review all modules and units.. Work on assignments and mini-projects..
Preparing for the exam
- Review all units, focusing on key definitions and formulas.
- Practice solving problems related to data presentation and analysis.
- Understand the different sampling techniques and their applications.
- Focus on hypothesis testing procedures and error analysis.
- Create summaries of each module to reinforce learning.
- Practice with past exam papers to get familiar with the question format.
Questions students ask about this course
What is STT102 about?
This course introduces students to the basic principles and applications of statistics. It is designed for students with no prior knowledge of statistics, initiating them to the subject at an introductory stage. The course covers data collection, compilation, analysis, and presentation, along with drawing conclusions from statistical analysis. It also uses practical examples from the local environment and case studies in the social and health sectors.
How many units does STT102 have?
STT102, Introductory Statistics, has 20 units across 4 modules, over 155 pages of course material. You can read it one unit at a time.
How many credit units is STT102?
STT102 carries 2 credit units, at 100 level in Sciences.
Is STT102 hard?
STT102 is rated beginner level, with intermediate mathematical content. It is mostly theoretical and case study work.
How long does STT102 take to study?
About 91 hours of study, spread across its 20 units.
How is STT102 assessed?
STT102 is assessed by Tutor Mark Assignments and Final Examination.
What can I do with STT102?
Nurse, Medical Researcher, Health Administrator, Public Health Officer and Data Analyst.