Friday 5 May 2023

Statistical Analysis: The use of Statistical Methods to Analyze Data and Draw Conclusions

Statistical Analysis: 

The use of Statistical Methods to Analyze Data and Draw Conclusions



The process of gathering and analysing data with the purpose of identifying patterns and trends is known as statistical analysis. It is a technique for eliminating bias from data evaluation by using numerical analysis. This method is beneficial for gathering research interpretations, creating statistical models, and organising surveys and studies.


In AI and ML, statistical analysis is a scientific tool that aids in the collection and analysis of massive volumes of data in order to spot recurring patterns and trends and turn them into actionable knowledge. Simply said, statistical analysis is a method for data analysis that assists in deriving meaningful conclusions from raw and unstructured information. 

Types of Statistical Analysis

Given below are the 6 types of statistical analysis:

1. Descriptive Analysis

Data must be gathered, comprehended, summarised, and statistically analysed in order to be presented as tables, charts, and graphs. It just makes the complicated data easier to read and understand, rather than offering any conclusions.


2. Inferential Analysis

Generating meaningful conclusions from the analysed data is the main goal of inferential statistical analysis. It investigates the connections between various factors or offers population-wide forecasts.

3. Predictive Analysis

A sort of statistical analysis known as predictive statistical analysis examines data to identify historical trends and make predictions about the future based on those trends. The statistical analysis of collected information is carried out using artificial intelligence, data mining, and machine learning techniques.


4. Prescriptive Analysis

Prescriptive analysis analyses data and recommends the appropriate course of action in light of the findings. It is a type of statistical study that aids in decision-making.. 

5. Exploratory Data Analysis

Exploratory analysis and Inferential analysis are similar, but exploratory analysis entails looking into unidentified data relationships. It examines any potential connections in the data.

6. Causal Analysis

Determine the cause and effect relationships between various variables contained within the raw data using causal statistical analysis. It establishes the cause of an event and its impact on other factors, to put it simply. Businesses can utilise this process to identify the cause of failure. 

Statistical Analysis Process

The five actions you should take to do a statistical analysis are listed below:

Step 1: The type of data that you are expected to analyse should be identified and described.

Step 2: The following step is to build a connection between the sample population to which the data belongs and the analysed data. 

Step 3: The third phase entails developing a model that concisely explains and illustrates the relationship between the population and the data.

Step 4: Show whether or not the model is accurate.

Step 5:To forecast anticipated future patterns and events, use predictive analysis. 


Statistical Analysis Methods

Although there are various methods used to perform data analysis, given below are the 5 most used and popular methods of statistical analysis:


1. Mean

One of the most widely used approaches to statistical analysis is the mean or average mean. The mean, which is fairly easy to calculate, determines the overall trend of the data. The mean is determined by adding up all the values in the data set, then dividing it by the total number of data points. Despite the simplicity of calculation and its advantages, it is not advisable to use the mean as the only statistical indicator because doing so can lead to erroneous judgements.


2. Standard Deviation

Another very popular statistical tool or procedure is standard deviation. It examines how far each data point deviates from the overall data set mean. It establishes how the data set's data are distributed around the mean. It can be used to determine whether or not the research findings are generalizable. 


3. Regression

Regression is a statistical technique that aids in establishing the causal connection between the variables. It establishes how a dependent variable and an independent variable are related. Future trends and events are typically predicted using it.


4. Hypothesis Testing

A conclusion or argument can be put to the test through hypothesis testing by comparing it to a set of data. The hypothesis, which was formulated at the outset of the study, may prove to be true or erroneous depending on the findings of the investigation.


5. Sample Size Determination

A technique used to extract a sample from the complete population that is representative of the population is sample size determination or data sampling. When the population is exceedingly huge, this strategy is employed. You can select from a number of data gathering strategies, including convenience sampling, random sampling, and snowball sampling.


Benefits of Statistical Analysis

Statistical analysis is a boon to humanity and offers many advantages for both people and businesses. Some of the justifications for investing in statistical analysis are listed below:


1. Making judgements will be simpler if you are able to calculate the monthly, quarterly, and annual sales profits and costs.

2. You'll be able to make wise decisions with its assistance.

3. You can use it to pinpoint the issue or reason for the failure and implement fixes. For instance, it can assist you determine the cause of a rise in overall expenditures and reduce unnecessary spending.

4. You can use it to carry out market research and create a winning marketing and sales strategy.

5. It enhances the effectiveness of several procedures.


 

The conclusions are reached via statistical analysis, which helps organisations make decisions and forecast the future based on historical trends. It is the science of gathering, examining, and presenting data in order to spot trends and patterns. Working with numbers is involved in statistical analysis, which is used by corporations and other institutions to analyse data to produce useful information.


👍Anushree Shinde  [ MBA] 

Business Analyst

10BestInCity.com Venture

anushree@10bestincity.com

10bestincityanushree@gmail.com

www.10BestInCity.com 

https://www.portrait-business-woman.com/2023/05/anushree-shinde.html



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#MachineLearning#ArtificialIntelligence#PredictiveModeling#ResearchMethods

#QuantitativeResearch#StatisticalInference#Mathematics#ScienceOfData#BusinessIntelligence

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