What are the 5 methods of statistical analysis?
Statistics is a mathematical study that deals with collection and analysis. steps include data collection, analysis of data, perception, and organization or summarization of data. Statistics is a form of applied mathematics that produces a set of studies from the obtained data. This mathematical analysis makes the dataset applicable for real life. Statistics has its dominance in the field of psychology, geology, weather forecast, etc. the data is collected either in quantitative or qualitative form.
Types of statistic data
There are majorly two types of statistics data. They are descriptive statistics and inferential statistics. Let’s learn about these two types in more detail,
1. Descriptive Statistics
This statistics provides a description of the population through numerical, graphs or tables by using the given data. It is further categorized as,
- The measure of central tendency
- Measure of variability
2. Inferential Statistics
This type of statistics makes predictions about the population based on the given sample data. Inferential statistics uses the method of probabilities to prepare a datasheet.
What are the 5 basic methods of statistical analysis?
Various datasets are with excessive data are categorized into different types. These datasets of studies are prepared by different methods of statistical analysis.
Mean or average is the most commonly used method to perform the statistical analysis. It is generally used in regard to research, academics, and sports. The calculation of mean involves adding up the given numbers and dividing them by the number of items.
The mathematical formula of mean is given by
∑x = sum of numbers
n = number of items
- Standard Deviation
Standard deviation is a method for statistical analysis that uses the spread of information around the mean. As when you are trying to calculate a standard deviation the most information used is by the mean.
The mathematical formula of Standard deviation is given by
n = number of data points in the population
σ = variance
μ = mean of the data
x = value of a dataset
∑ = sum of data
σ = symbol of standard deviation
In statistical analysis methods, regression is a connection between an independent variable and a dependent variable. The lines used in the graphs of the regression chart show the connections between factors and time.
The mathematical formula of regression is given by
Y=a + b(x) is the equation of the slope.
Y = independent variable
b = slope
x = dependent variable
a = y-intercept
The formula is,
Yi = f (Xi, β) + ei
Yi = dependent variable
Xi = Independent variable
e = error terms
β = unknown parameters
- Hypothesis testing
Hypothesis testing is also widely known as ‘T Testing’ is a statistical analysis method that works on contrasting the given information against different assumptions. It is an estimation that is made for business purposes.
The mathematical formula of hypothesis testing is given by,
- Sample Size Determination
Sample size determination is a method of examining information from an excessive dataset. The given is so enormous that it is hard to gather exact information for every dataset.
Question 1: What are the requirements to find a standard deviation?
There are the following requirements to find a standard deviation
- Determine the mean of the numbers within the data set
- For each number within the data set, subtract the mean and square the result (formula (x − μ)2).
- Calculate the mean of those squared differences
- Take the square root of the final answer
Question 2: What is an inferential statistical analysis used for?
Inferential statistical analysis is used to study the relationship between variables and data which are used for making predictions or assumptions about the population.
Question 3: Find the mean value of the given data 4, 12, 16, and 24.
Sum of the number(x) = 4 + 12 + 16 + 24 = 56
Number of items(n) = 4
X = ∑x/n
X = 56/4
X = 14