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Statistics is a term that is used to compile a process that an analyst uses to distinguish a data set. Statistical analysis includes the process of collecting and calculating data and then compiling the data into one mathematical form. This method is used to analyze large volumes of data and their following properties. There are two types of statistical methods used in the analyzes of data namely descriptive statistics and inferential statistics.
Descriptive statistics: Descriptive statistics is a terms which analyze the data and represent it. Descriptive statistics is further divided into four types:
• Frequency: Percent, Count and Frequency are the terms which come under this category.
• Central Tendency: Mean, Median and Mode are the terms which come under this category.
• Variation: Range, Standard Deviation and Variance are the terms which come under this category.
• Position: Quartile Ranks and Percentile Ranks are the terms which come under this category.
Inferential statistics: Inferential statistics is utilized only when the data is viewed as subclass for particular population. Inferential statistics is further divided into three types:
• ANOVA (Analysis of Variance)
Software’s used in statistics are STATA, SPSS and SAS.
The different areas of applications of statistics are:
- Actuarial Sciences
- Operations Research
- Environmental Statistics
- Business Analytics
- Quality Control
- Statistical Mechanics
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- Descriptive statistics
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- Statistical inference Sampling distributions
- Statistical inference (2) Statistical tests
- Linear models in statistics
- Data and its graphical representation
- Drawing a histogram
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- What is statistical inference?
- Three types of statistical inference problems
- Estimation of a parameter
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- Estimation of the binomial parameter
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- The paired two sample t test
- T test for the parameters of SLR
- Non-parametric (= distribution-free) tests
- The Wilcoxon signed-rank test