Here you will learn what is combined mean formula and how to find combined mean with examples. Let’s begin – Combined Mean Formula If \(\bar{x_1}\) and \(\bar{x_2}\) be the means of two groups having \(n_1\) and \(n_2\) terms respectively then the mean(combined mean) of their composite group is given by Combined mean = \(n_1\bar{x_1} + […]
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Here you will learn what is weighted mean formula and how to calculate weighted mean with examples. Let’s begin – Weighted Mean Formula If \(w_1\), \(w_2\), ……\(w_n\) are the weights assigned to the values \(x_1\), \(x_2\), …..\(x_n\) respectively then their weighted mean is defined as Weighted mean = \(w_1x_1 + w_2x_2 +……+ w_nx_n\over {w_1 +…….+
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Here you will learn what is the formula for mode of grouped and ungrouped data and how to find mode with examples. Let’s begin – What is Mode ? Mode is the size of the variable which occurs most frequently. Formula for Mode : (i) For ungrouped distribution : The value of that variate which is
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Here you will learn what is the formula for median of grouped and ungrouped data and how to find median with examples. Let’s begin – What is Median ? Median is defined as the measure of central term when they are arranged in ascending or descending order of magnitude. Formula for Median : (i) For
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Here you will learn what is the formula for mean of grouped and ungrouped data and how to find mean with examples. Let’s begin – The formula for mean median and mode for grouped and ungrouped frequency distribution is given below. Formula for Mean : (i) For ungrouped distribution : If \(x_1\), \(x_2\), …… \(x_n\) are
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Here you will learn what is the mean deviation formula with examples. Let’s begin – Mean Deviation Formula (i) For Ungrouped distribution : Definition : If \(x_1\), \(x_2\), ….. , \(x_n\) are n values of a variable X, then the mean deviation from an average A (median or arithmetic mean) is given by Mean Deviation
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Here you will learn some statistics examples for better understanding of statistics concepts. Example 1 : If mean of the seies \(x_1\), \(x^2\), ….. , \(x_n\) is \(\bar{x}\), then the mean of the series \(x_i\) + 2i, i = 1, 2, ……, n will be- Solution : As given \(\bar{x}\) = \(x_1 + x_2 +
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Here you will learn how to solve mean by using step deviation method and by short method and properties of mean. Let’s begin – Mean By Short Method If the value of \(x_i\) are large, then calculation of A.M. by using mean formula is quite tedious and time consuming. In such case we take deviation
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Here you will learn mean square deviation formula and relation between mean square deviation and variance with example. Let’s begin – Mean Square Deviation Formula The mean square deviation of a distribution is the mean of the square of deviations of variate from assumed mean. It is denoted by \(S^2\). Hence \(S^2\) = \(\sum{x_i –
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Here, you will learn what are the measures of dispersion in statistics i.e. range, mean deviation, variance and standard deviation with example. Let’s begin – Measures of Dispersion : The dispersion of a statistical distribution is the measure of deviation of its values about the their average(central) value. It gives an idea of scatteredness of
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