Verified

Masters of Science @ Andhra University

** I can Teach: **

Theory of Probability, Simple Random Sampling, Charts and Diagrams, Variance, Standard Deviation, Skewness, Kurtosis, Percentiles and Quartiles, Coefficient of Variance, Mean

I have 5 years of teaching experience in statistics.

I am working as an Assistant professor for Basic Science and Humanities in the specialization of Statistics in the Avanthi Engineering college, vizag.

I taught different papers like,

1. Quantitative techniques

2. Business research methods,

3. Statistics and probability.

4. Linear models

5. Basic Statistics

6. CA-CPT statistics

7. Engineering Statistics

8. MBA statistics

9. Operations research

Theory of Probability

Simple Random Sampling

Charts and Diagrams

The chance of occurrence is called as probability. The probability is depends chance events and it always lies between 0 and 1. The calculated probability value is 0 then it called impossible event. The calculated probability value is 1 then it called certain event. The probability has many branches like conditional probability, addition of probability, multiplication of probability joint probability and random variables. This probability involves in every where like sampling, queuing etc.

It is a sampling technique to draw a sample from the population. In this process every unit in the population has an equal probability of selected as a sample. The simple random sampling is divided as two ways like simple random sampling with replacement and simple random sampling without replacement.

The mean is described as a single term that can be represented as whole data. This is very basic and important measure of central tendency. This is not calculated for open ended classes.

The median is described as middle number of ascending order of the data when data series is odd (Or) the simple average of middle two numbers of ascending order of data when data series is even. This is also important measure of central tendency and it is also calculated for open ended classes.

The distributions t, F and Z are belongs to sampling distributions. The t and Z distributions are very similar and have same characteristics but have small difference. If sample size n is greater than 30 and population standard deviation is known then use Z distribution. if sample size is less than or equal to 30 and population standard deviation is not known then use t distribution. Both distributions are used to test the single and difference of means. The F test is used to test the difference between the two population variances. The F test is used to test the difference of more than two means like ANOVA. ANOVA is connected with F distribution.

Correlation is used to explain there exists a relationship between two variables. The correlation is 3 types like positive, negative and un-correlation. If the two events are deviate in the same direction then it is called positive correlation. If the two events are deviate in the opposite direction then it is called negative correlation. If the two events are deviate in the different directions then it is nu-correlation. The average relationship is called regression. This concept is used for forecasting and regression can be used when the correlation must be exists between two variables. The regression can be used for two variables or more than two variables. If the regression is used for more than 2 variables then it is called multiple regression.

5 star

15 May, 2020

5 star

was great

14 Apr, 2020

5 star

Very hard working! A god of statistics! thank you so much for doing the work in a very limited time frame! He completed my work in 1 hour exactly. Thank you so much, Sir!

12 Apr, 2020

5 star

it's good

27 Mar, 2020

5 star

it was excellent

26 Mar, 2020

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