Statistics Study Notes PDF
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These notes provide an overview of basic statistical concepts. It covers various types of data (primary, secondary, quantitative, qualitative, nominal, ranked, discrete, continuous). It also explains correlation, regression, measures of central tendency (mean, median, mode), measures of dispersion (variance, standard deviation, etc.), and probability. The notes also include a discussion of limitations of statistics.
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**Statistics** It is a branch of mathematics that deals with the collection, analysis, interpretation, presentation and organization of data. **Descriptive** It is a type of statistics that deals with the presentation and description of data in a meaningful way. **Inferential** It involves maki...
**Statistics** It is a branch of mathematics that deals with the collection, analysis, interpretation, presentation and organization of data. **Descriptive** It is a type of statistics that deals with the presentation and description of data in a meaningful way. **Inferential** It involves making inferences about a population based on sample data. **Primary** It is a type of data that is directly collected by the researcher for a specific purpose **Secondary** They are pre-existing data that is already been collected by others **Quantitative data** They are numerical data that can be measured and quantified. E.g. height, age, weight. **Qualitative** They are non-numerical data that described qualities. It is used to describe values that cannot be measured or quantified. E.g. colors of waters, types of material, interview transcript. **Nominal** They are data that can be categorized without any specific order. E.g. gender, marital status, ratings. **Ranked** It is an ordinal data that can be categorized based on specific order. E.g. ranking, educational level. **Discrete data** It is a numerical data that can only take specific value **Continuous data** It is a numerical data that can take any value within a range **Correlation and regression ore two sides of the same coin explain** Correlation measures the strength of a relationship between variables while regression predict one variable based on another. Correlation is symmetric and regression is asymmetric. Both analyze relationship making them two sides of the same coin. **What is regression?** **Regression is a statistical tool used to predict one variable using other variables. E.g. if data shows that advertising leads to higher sales, managers can use regression analysis to plan budget and predict future sales.** **What is measure of central tendency?** **It is a statistical tool used to measure the center or average of a data set. There are three main types: mean, median and the mode.** **What is dispersion?** **Dispersion is the spread of data point in a data set. The difference measures of dispersion are: range, variance and standard deviation** **Statistics is all-pervading. Explain** **Statistics can be used in various fields like research, data science, business, medicine, for data analysis and decision-making, making it all pervading.** **Explain what do you understand by the term probability** Probability is the measure of how likely an event is to occur, expressed as a value between 0 and 1, where 0 means impossible and 1 means certain**.** **limitations of statistics** **Does Not Deal with Individual Items -- Statistics focuses on groups, not individuals.** **Deals Only with Quantitative Data -- It cannot measure qualities like honesty or intelligence.** **Statistical Laws Are True Only on Averages -- Conclusions are based on averages not individual cases.** **Does Not Reveal the Whole Story -- Data can be misrepresented or misleading.** **Can Be Misused -- Incorrect use can lead to false conclusions.** **Requires Uniform and Homogeneous Data -- Data must be consistent for accurate results**