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M.sc @ Shivaji University Kolhapur

Watching Movies, and Music, Reading popular statistics books, Cooking

Trigonometry, Algebra Basics, Algebra, Geometry, Probability and Statistics, Precalculus, Differential Calculus, Integral Calculus, Linear Algebra, Multivariable Calculus

I have great passion for tutoring and have been tutoring Mathematics and Statistics for the past 5 years. I not only aim to help students understand the concepts, but also make the learning process more enjoyable.

- Trigonometry
- Algebra Basics
- Algebra

The probability of an event is a number indicating how likely that event will occur. This number is always between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

Simple random sampling is the basic sampling technique where we select a group of subjects or a sample for study from a larger group or a population. Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample

There are several different types of charts and graphs. The four most common are probably line graphs, bar graphs and histograms, pie charts, and Cartesian graphs. They are generally used for, and best for, quite different things

Variance describes how much a random variable differs from its expected value. The variance is defined as the average of the squares of the differences between the individual (observed) and the expected value.

Standard deviation is a number used to tell how measurements for a group are spread out from the average (mean), or expected value. A low standard deviation means that most of the numbers are close to the average. A high standard deviation means that the numbers are more spread out.

Types of Skewness. Broadly speaking, there are two types of skewness: They are (1) Positive skewness and (2) Negative skewnes. Skewness refers to distortion or asymmetry in a symmetrical bell curve, or normal distribution, in a set of data. If the curve is shifted to the left or to the right, it is said to be skewed. Skewness can be quantified as a representation of the extent to which a given distribution varies from a normal distribution.

Percentiles A percentile is a measure at which that percentage of the total values are the same as or below that measure. For example, 90% of the data values lie below the 90th percentile, whereas 10% of the data values lie below the 10th percentile. Quartiles Quartiles are values that divide a (part of a) data table into four groups containing an approximately equal number of observations. The total of 100% is split into four equal parts: 25%, 50%, 75% and 100%. The first quartile (or lower quartile), Q1, is defined as the value that has an f-value equal to 0.25. This is the same thing as the twenty-fifth percentile. The third quartile (or upper quartile), Q3, has an f-value equal to 0.75. The interquartile range, IQR, is defined as Q3-Q1.

The coefficient of variation represents the ratio of the standard deviation to the mean, and it is a useful statistic for comparing the degree of variation from one data series to another, even if the means are drastically different from one another.

The statistical mean refers to the mean or average that is used to derive the central tendency of the data in question. It is determined by adding all the data points in a population and then dividing the total by the number of points.

The median is a simple measure of central tendency. To find the median, we arrange the observations in order from smallest to largest value. If there is an odd number of observations, the median is the middle value. If there is an even number of observations, the median is the average of the two middle values.

The number which appears most often in a set of numbers. Example: in {6, 3, 9, 6, 6, 5, 9, 3} the Mode is 6 (it occurs most often).

Correlation is used to represent the linear relationship between two variables. On the contrary, regression is used to fit the best line and estimate one variable on the basis of another variable. ... As opposed to, regression reflects the impact of the unit change in the independent variable on the dependent variable.

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