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Statistical Aid

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Statistical Aid

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Statistical Aid is a site that provides statistical content, data analysis content, and also discusses the various fields of statistics.

Lean more about:

1. Machine learning & Data Science

2. Basic Statistics

3. Statistical Sampling

4. Probability Distribution

5. Non Parametric Test

6. Data Science Blog

Basic Statistics

Basic statistics is a branch of mathematics that focuses on the collection, analysis, interpretation, and presentation of data. It involves understanding key concepts like descriptive statistics, which summarize data using measures such as the mean, median, mode, range, and standard deviation to provide insights into data trends and variability. Additionally, inferential statistics allows us to make predictions or generalizations about a population based on sample data, using methods like hypothesis testing and confidence intervals. Data visualization, through tools such as graphs and charts, plays an important role in presenting information clearly, helping identify patterns or anomalies. This foundation of statistical techniques is widely applicable in fields like economics, medicine, engineering, social sciences, and business, enabling researchers and professionals to make informed decisions, evaluate risks, and draw meaningful conclusions from both small and large datasets.

A probability distribution is a mathematical function that describes the likelihood of different outcomes in a random experiment or event.

Probability sampling ensures that every individual in the population has a known, non-zero chance of being selected.

Non-probability sampling doesn't offer each member of the population an equal chance of selection. Methods like convenience sampling, where participants are selected based on availability, or purposive sampling, where specific individuals are chosen for a particular purpose, fall under this category.

Data analysis using SPSS (Statistical Package for the Social Sciences) involves the use of this software to organize, analyze, and interpret data in a variety of fields, including social sciences, healthcare, and business.

Data analysis using spss
Data input in spss
Import data in spss
Sort data using spss
Merge data file in spss
Combine data set in spss
Missing value in spss
Variable transformation in spss
Univariate analysis in spss
Bivariate analysis in spss
Normality of data in spss

Data Analysis Using Stata

Data Analysis Using R/R Studio

Machine Learning and Data Science

There are also some other topics as follows:

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