The Best Guide of Statistical Analysis for In-depth Understand

13 Sep 2022 3550 share it:

A Scholar’s Handbook to Understanding Statistical Analysis

Statistical analysis, Big Data, DevOps, SAAS, are some of the hot topics in today’s time. Every economist is well aware of the fact that by decade, these are going to be the powerful rulers of our world. Right from our day-to-day activities to businesses of the developing cities, everything is based on statistics and statistical analysis. With such rapid growth in this sector, you can’t leave a chance to stand back, right? So, experts of Assignment Prime have brought you this blog that includes everything you need to know about this game-changer.

Let us now begin right from the basics by looking into what is statistics and its purpose before proceeding further into the topic.

What Is Statistical Analysis?

The typical statistics definition goes like “It is a discipline which deals with collecting, analyzing, organizing, interpreting and presenting data for various purposes.” The best thing is this approach is applied to almost every field be it is industrial, scientific or social.

Statistical analysis is the process of collecting, analyzing, organizing, interpreting, and presenting data in a way that you can find patterns and trends in them. You might have heard this a ton of times from the great economists of the US, Canada and such. The reason behind this getting such hype is its application in a vast area. Here are some fields of statistics, where this can be applied.

These are different fields of statistics out of the numerous others where analysis can be put into practice. Statistic analysis plays a key role in how things are improvising with time; how taking appropriate decisions is contributing to the development of the country. Read the following section to know the purpose of this analysis.

What Is the Primary Function of Statistical Analysis?

The prime motive or purpose behind the statistical analysis is:

• To summarize the data
• To interpret data with accuracy
• To simplify complex data
• To find key measures
• To calculate measures
• To study past actions
• To make future predictions
• To correlate and compare different data
• To test the experiment’s hypothesis

These are the motives for performing this analysis. Now, let us take a look into different types of statistical analysis.

What Are the Types of Statistical Analysis?

Though there are 7 types of statistical analysis, we mainly focus on two types. Here, we shall look into the 2 main types in detail and know the 5 types in brief.

A. Predictive statistics

It uses statistical algorithms and machine learning techniques to predict future results or behaviour based upon the decisions made in the history.

B. Prescriptive statistics

Prescriptive analytics is used to provide optimal advice for the decision-making process.

C. Causal statistics

This is used to know ‘why’ or the reason behind anything to investigate the root cause or key problem.

D. Exploratory data statistics

Exploratory data analysis is used to identify general patterns to find out answers for unknown relationships to discover new connections.

E. Mechanistic statistics

The mechanistic analysis is about making changes in variables which lead to modifications in other variables while neglecting the external influences.

F. Descriptive statistics

It is used to describe the data collected from a particular population and summarize it in a rational way.

G. Inferential statistics

Inferential Analytics is used to study the relationship between variables within a broader  population.

These are the different types of statistical analysis. Now let us take a look into descriptive vs inferential statistics.

Descriptive Statistics vs Inferential Statistics

This was all about descriptive vs inferential statistics. Now, let us take a look at how to do statistical analysis.

How Do You Do Statistical Analysis?

Here is a simple 5-step process for conducting statistical analysis.

1. Begin with describing the nature of the data that you will be analyzing.

2. Now, explore the relation of this data to the underlying population.

3. Use data modeling to summarize the data and what you have understood about its relationship with the underlying population.

4. Here, you either prove or disapprove the validity of the above-suggested model.

5. Finally, employ predictive analytics that can help you in making futuristic decisions.

This is a simple 5-step process that you need to follow for statistical analysis. If how to do strategic management analysis is your concern, then our writers can help you with strategic management on TESCO, Coca Cola and Toyota.

Now, the next concern is what are the different statistical analysis software or methods that you should use; which we discussed in the next section.

What Are Top 5 Statistical Analysis Software?

Here we listed below top 5 Statistical Analysis Software that you can use to get accurate results.

1. AcaStat

It can be used for Mac and windows. It is one of the best statistical analysis tools available online.

2. IBM SPSS

This is a software from IBM that provides text analysis, entity analysis, automated modelling, decision management and development.

3. MaxStat

It is easy to use software that provides analysis in just 3-simple steps. It is also one of the most affordable software available online.

4. MINITAB

It is one of the most popular and commonly used software with more than 90% companies and schools, colleges using it for analyzing and collecting data.

5. NCSS

It includes a large number of statistical and graphical tools that facilitate analyzing the data.

These are the top 5 software that you can use to get accurate results from your process. Now, let us look into some methods.

What Are Top 5 Statistical Analysis Methods?

Here are the top 5 statistical Analysis Methods that you can implement for a hassle-free calculation process.

1. Hypothesis testing

It is used to assess if a certain premise is actually true for a particular data set or population.

2. Mean

It is used to calculate an average by summing up the items in the list and dividing it by the number of items.

3. Regression

It is used to model the relationships between dependent and explanatory variables that are charted on a scatterplot.

4. Sample size determination

It is used to take an appropriate sample and perform the analysis on the same to determine and measure a large data set.

5. Standard Deviation

It is used to measure the spread of the data around the mean where high standard deviation signifies that the data is widely spread while the low deviation represents more data alignment with the mean.

These are the top 5 statistical analysis methods. Now that you know these let us look into the applications of this process.

What Are the Practical Application of Statistics?

Here, we listed down below some important applications of statistics.

1. Research interpretation

It helps researchers to understand their findings, reject or approve theories and arrive at conclusions.

2. A meta-analysis of literature review

It facilitates analyzing and summarizing the content from different studies and coming to a common conclusion.

3. Clinical trial and design

It can be used for clinical trial and design at times of discovering new medicines and testing them on a small group.

4. Designing surveys

This is one of the topmost statistics applications. It can be used to collect data or information during surveys in bulk and analyze them to arrive at appropriate conclusions.

5. Statistical modeling

It can be used to build predictive models based on the data from history, the patterns and trends followed for futuristic decision making.

These are the top 5 uses and applications of statistics. You can learn about these in detail from the experts of Assignment Prime. Wondering how? Keep reading to know.

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