Preparing for the CUET Statistics exam requires a clear understanding of statistical formulas. Many questions in the exam are based directly on formulas, so students must revise them regularly.

A CUET Statistics formulas list helps students remember important formulas and quickly revise the syllabus before the exam. Instead of searching formulas in many books, students can use a single formula guide.

In this article, we will cover important formulas from topics such as probability, central tendency, dispersion, correlation, and data analysis.

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Probability Formulas

Probability is one of the most important topics in statistics. It measures the chance that an event will happen.

The basic probability formula is:

P(A) = \frac{n(A)}{n(S)}

Where

• $P(A)$P(A) = probability of event A
• $n(A)$n(A) = number of favorable outcomes
• $n(S)$n(S) = total outcomes

Students often use this formula to calculate the probability of simple events.

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Addition Rule of Probability

When two events occur together, the addition rule is used.$$P(A \cup B) = P(A) + P(B) – P(A \cap B)$$P(A∪B)=P(A)+P(B)−P(A∩B)

This formula is helpful when events overlap.

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Conditional Probability

Conditional probability measures the probability of an event given that another event has already occurred.$$P(A|B) = \frac{P(A \cap B)}{P(B)}$$P(A∣B)=P(B)P(A∩B)​

This formula is widely used in statistical analysis.

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Measures of Central Tendency Formulas

Central tendency describes the center of a dataset. The three main measures are mean, median, and mode.

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Arithmetic Mean

The mean is the average value of a dataset.$$\bar{x} = \frac{\sum x}{n}$$xˉ=n∑x​

Where

• $x$x = data values
• $n$n = number of observations

Mean is one of the most commonly used statistical measures.

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Median

The median is the middle value when data is arranged in order.

For grouped data:$$Median = L + \left(\frac{\frac{n}{2} – c}{f}\right)h$$Median=L+(f2n​−c​)h

Where

• $L$L = lower boundary
• $c$c = cumulative frequency
• $f$f = frequency of median class
• $h$h = class width

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Mode

Mode is the value that appears most frequently in the dataset.

For grouped data:$$Mode = L + \frac{(f_1 – f_0)}{(2f_1 – f_0 – f_2)} \times h$$Mode=L+(2f1​−f0​−f2​)(f1​−f0​)​×h

Where

• $f_1$f1​ = frequency of modal class
• $f_0$f0​ = frequency before modal class
• $f_2$f2​ = frequency after modal class

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Measures of Dispersion Formulas

Dispersion shows how spread out the data values are.

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Range

Range is the difference between the highest and lowest values.$$Range = Maximum – Minimum$$Range=Maximum−Minimum

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Variance

Variance measures how far data points are from the mean.

\sigma^2 = \frac{1}{N}\sum_{i=1}^{N}(x_i – \mu)^2

Where

• $\mu$μ = mean
• $N$N = total observations

Variance is useful for understanding variability in data.

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Standard Deviation

Standard deviation is the square root of variance.$$\sigma = \sqrt{\sigma^2}$$σ=σ2​

It measures how much data deviates from the mean.

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Correlation Formulas

Correlation measures the relationship between two variables.

The Pearson correlation coefficient formula is:$$r = \frac{\sum (x-\bar{x})(y-\bar{y})}{\sqrt{\sum (x-\bar{x})^2 \sum (y-\bar{y})^2}}$$r=∑(x−xˉ)2∑(y−yˉ​)2​∑(x−xˉ)(y−yˉ​)​

Where

• $r$r = correlation coefficient
• $x$x and $y$y = variables

Correlation values range between -1 and +1.

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Regression Formulas

Regression is used to predict the relationship between variables.

Regression equation:$$y = a + bx$$y=a+bx

Where

• $a$a = intercept
• $b$b = regression coefficient

Regression helps estimate unknown values based on known data.

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Index Number Formulas

Index numbers measure changes in variables over time.

Simple price index formula:$$Index = \frac{Current\ Price}{Base\ Price} \times 100$$Index=Base PriceCurrent Price​×100

Index numbers are commonly used in economics and statistics.

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Sampling Formulas

Sampling helps analyze a large population using a smaller group.

Sample mean formula:$$\bar{x} = \frac{\sum x}{n}$$xˉ=n∑x​

Variance of sample mean:$$Var(\bar{X}) = \frac{\sigma^2}{n}$$Var(Xˉ)=nσ2​

Where

• $n$n = sample size.

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Standard Score (Z-Score)

The Z-score measures how many standard deviations a value is from the mean.

$z = \frac{x – \mu}{\sigma}$z=σx−μ​

$x$x

$\mu$μ

$\sigma$σ

$z=\frac{x-\mu}{\sigma}\approx 1.2$z=σx−μ​≈1.2

$\Phi(z)\approx 88.5\%$Φ(z)≈88.5%

Where

• $x$x = data value
• $\mu$μ = mean
• $\sigma$σ = standard deviation

This formula is useful in normal distribution analysis.

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Tips to Remember CUET Statistics Formulas

Students should revise formulas regularly during preparation.

Helpful tips include:

• Write formulas in short notes
• Revise formulas daily
• Practice numerical problems
• Use mock tests to apply formulas

Regular practice helps students remember formulas during the exam.

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Why Learning Formulas is Important for CUET Statistics

Formulas play a key role in solving statistics problems.

Benefits of learning formulas include:

• Faster problem solving
• Better exam performance
• Strong concept understanding
• Easy revision before the exam

Students who practice formulas regularly often perform better in the exam.

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Conclusion

Preparing for the CUET Statistics exam becomes easier when students understand and revise important formulas. Topics such as probability, central tendency, dispersion, correlation, and regression are important parts of the syllabus.

Using a well-organized CUET Statistics formulas list helps students revise quickly and improve confidence before the exam. With consistent practice and proper revision, students can perform well in the CUET Statistics exam.