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Introduction to Statistics

Statistics is the practice or science of collecting and analysing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.

There are two broad categories in statistics:

  • Descriptive statistics
  • Inferential statistics
Introduction to Statistics

Descriptive Statistics

Descriptive statistics summarises and organises data so that it can be easily understood. Its purpose is to give a clear overview of the main features of a data set.

Descriptive Statistics

Categories of Descriptive Statistics

  • Measures of Central Tendency - locate the centre or typical value of a distribution (for example: mean, median, mode).
  • Measures of Dispersion or Variation - describe how spread out the values are (for example: range, variance, standard deviation).
  • Measures of Position - describe relative standing of values in a distribution (for example: percentiles, quartiles, rank scores).

Measures of Central Tendency

  • Measures of central tendency refer to a value that represents the centre point of a data set.
  • The most commonly used measures are mean, median, and mode.

Mean

The arithmetic mean (often called the average) of a set of numbers is the sum of the elements divided by the number of elements.

Formula:

Mean = Sum of all elements ÷ Number of elements

Example

Q. Tom scored 88 in English, 97 in Math, 90 in Science and 85 in Social Studies. Calculate his average marks.

Solution:

Mean = (88 + 97 + 90 + 85) ÷ 4

Mean = 360 ÷ 4

Mean = 90

MULTIPLE CHOICE QUESTION

Try yourself: The  arithmetic mean of 4,6,8 is

A

4

B

6

C

8

D

4.5

Median

The median of a data set is the middle value when the numbers are arranged in ascending or descending order. If the number of observations is even, the median is the mean of the two middle values.

  • When a data set has an odd number of elements, take the middle value.
  • When a data set has an even number of elements, take the average of the two middle values.

Examples

Q.1. Find the median of the set {4, 7, 1, 0, 9}.

Solution:

Arrange in order: {0, 1, 4, 7, 9}

Median = 4

Q.2. Find the median of the set {3, 2, 5, 10, 8, 7}.

Solution:

Arrange in order: {2, 3, 5, 7, 8, 10}

Median = (5 + 7) ÷ 2

Median = 6

Note: When a set is evenly spaced (the difference between consecutive elements is constant), the mean and the median are equal.

Q.3. Find the mean and median of the set {4, 8, 10, 6}.

Solution:

Mean = (4 + 8 + 10 + 6) ÷ 4

Mean = 28 ÷ 4

Mean = 7

Arrange in order: {4, 6, 8, 10}

Median = (6 + 8) ÷ 2

Median = 7

MULTIPLE CHOICE QUESTION

Try yourself: The George family drove through 11 states on their Spring vacation. Gasoline prices varied from state to state. Find the median gasoline price.
42,54,12,89,56,75,29,13,20,11,34

A

20

B

29

C

54

D

34

Mode

The mode of a data set is the value that appears most frequently. A set can have one mode (unimodal), more than one mode (multimodal or bimodal), or no mode.

Examples

Q.1. 3, 4, 7, 3, 1, 2, 3, 9, 13

Solution: Mode = 3

Q.2. 21, 34, 9, 57, 64, 34, 90, 9, 12, 2, 34, 9

Solution: Modes = 34 and 9 (bimodal)

Q.3. 6, 7, 36, 2, 1, 41

Solution: No mode (all values occur once)

Q.4. The mean of 2, 6, 9, 13, x is 9. Find the median of {22, x, 38, 11, 5, 9}.

Solution:

(2 + 6 + 9 + 13 + x) ÷ 5 = 9

30 + x = 45

x = 15

Arrange the second set: {5, 9, 11, 15, 22, 38}

Median = (11 + 15) ÷ 2

Median = 13

Measures of Dispersion

Dispersion measures describe how stretched or squeezed a distribution is. We focus on two common measures: range and standard deviation.

Range

The range is the simplest measure of dispersion; it is the difference between the largest and smallest values in the data set.

Example: For {3, 4, 10, 14, 8}, Range = 14 - 3 = 11.

Standard Deviation

The standard deviation quantifies the average distance of data points from the mean. It is the square root of the variance. The usual calculation steps are:

  • Find the arithmetic mean of the data set.
  • Find each value's deviation from the mean (value - mean).
  • Square each deviation.
  • Find the mean of the squared deviations (this is the variance).
  • Take the square root of the variance to obtain the standard deviation.

Example. Calculate the standard deviation for the set {3, 4, 8, 10}.

Solution:

Find the mean.

Mean = (3 + 4 + 8 + 10) ÷ 4

Mean = 25 ÷ 4

Mean = 6.25

Find deviations from the mean for each number.

3 - 6.25 = -3.25

4 - 6.25 = -2.25

8 - 6.25 = 1.75

10 - 6.25 = 3.75

Square each deviation.

(-3.25)² = 10.5625

(-2.25)² = 5.0625

(1.75)² = 3.0625

(3.75)² = 14.0625

Find the mean of the squared deviations (variance).

Variance = (10.5625 + 5.0625 + 3.0625 + 14.0625) ÷ 4

Variance = 32.75 ÷ 4

Variance = 8.1875

Take the square root of the variance to get the standard deviation.

Standard deviation = √8.1875

Standard deviation ≈ 2.86 (rounded to two decimal places)

Inferential Statistics

  • Inferential statistics uses a sample of data to make generalisations or predictions about a larger population.
  • It provides methods to estimate population parameters, test hypotheses, and make predictions with quantifiable uncertainty.
  • To select representative samples, common sampling techniques include simple random sampling, stratified sampling, cluster sampling, and systematic sampling.
Inferential Statistics

Some Solved Questions

Q.1. If the mean of numbers 28, x, 42, 78 and 104 is 62, what is the mean of 48, 62, 98, 124, and x?

a) 78

b) 58

c) 390

d) 310

e) 66

Answer: Option A

Solution:

Find the sum of the four known numbers in the first series (excluding x).

Sum = 28 + 42 + 78 + 104

Sum = 252

Find the sum of the four known numbers in the second series (excluding x).

Sum = 48 + 62 + 98 + 124

Sum = 332

Difference in sums = 332 - 252

Difference = 80

Since each series has 5 numbers, the difference in average = 80 ÷ 5

Difference in average = 16

Average of the first series = 62

Average of the second series = 62 + 16

Average of the second series = 78

Alternative approach: Each of the four known numbers in the new series is 20 greater than the corresponding known number in the first series; this increases the total by 4 × 20 = 80, and so the average increases by 80 ÷ 5 = 16, giving 78.

Q.2. The arithmetic mean of the 5 consecutive integers starting with 's' is 'a'. What is the arithmetic mean of 9 consecutive integers that start with s + 2 ?

a) 2 + s + a

b) 22 + a

c) 2s

d) 2a + 2

e) 4 + a

Answer: Option E

Solution:

The mean of 5 consecutive integers is the middle (third) term.

The five terms are s, s + 1, s + 2, s + 3, s + 4.

Thus a = s + 2.

The nine consecutive integers starting from s + 2 are:

s + 2, s + 3, s + 4, s + 5, s + 6, s + 7, s + 8, s + 9, s + 10.

The mean of nine consecutive integers is the middle (fifth) term, which is s + 6.

Since a = s + 2, the required mean = a + 4.

Alternative (check) approach:

Assume s = 1 to verify.

Five numbers: 1, 2, 3, 4, 5 → mean = 3, so a = 3.

Nine numbers starting at s + 2 = 3: 3, 4, 5, 6, 7, 8, 9, 10, 11 → mean = 7 = 3 + 4 = a + 4.

Q.3. The average weight of a group of 30 friends increases by 1 kg when the weight of their football coach was added. If the average weight of the group after including the weight of the football coach is 31 kg, what is the weight of their football coach?

a) 31 kg

b) 61 kg

c) 60 kg

d) 62 kg

e) 91 kg

Answer: Option B

Solution:

Old average (without coach) = 31 - 1

Old average = 30 kg

Total weight of 30 friends = 30 × 30

Total weight = 900 kg

Total weight after including coach = 31 × 31

Total weight = 961 kg

Weight of coach = 961 - 900

Weight of coach = 61 kg

DescriptionNumberAverageSum
Without Coach3030900
With Coach3131961
Weight of Coach961 - 900 = 61 kg

Q.4. The average wages of a worker during a fortnight comprising 15 consecutive working days was $90 per day. During the first 7 days, his average wages was $87/day and the average wages during the last 7 days was $92 /day. What was his wage on the 8th day?

a) $83

b) $92

c) $90

d) $97

e) $104

Answer: Option D

Solution:

Total wages for 15 days = 15 × 90

Total wages = $1350

Total wages for first 7 days = 7 × 87

Total wages = $609

Total wages for last 7 days = 7 × 92

Total wages = $644

Total for all 15 days = wages for first 7 days + wage on 8th day + wages for last 7 days

1350 = 609 + wage on 8th day + 644

Wage on 8th day = 1350 - 609 - 644

Wage on 8th day = $97

Some Solved Questions

Q.5. The average of 5 numbers is 6. The average of 3 of them is 8. What is the average of the remaining two numbers?

a) 4

b) 5

c) 3

d) 3.5

e) 0.5

Answer: Option C

Solution:

Sum of all 5 numbers = 5 × 6

Sum = 30

Sum of the 3 numbers = 3 × 8

Sum = 24

Sum of the remaining two numbers = 30 - 24

Sum = 6

Average of the two numbers = 6 ÷ 2

Average = 3

Summary (optional)

This chapter introduced the basic ideas of statistics: how data can be described using measures of central tendency (mean, median, mode), how dispersion is measured (range, variance, standard deviation), and the distinction between descriptive and inferential statistics. Worked examples and solved questions demonstrate standard methods for computing averages, medians, modes, and standard deviation, and illustrate common problem-solving frameworks used in competitive and school examinations.

The document Introduction to Statistics is a part of the SSC CGL Course SSC CGL Tier 2 - Study Material, Online Tests, Previous Year.
All you need of SSC CGL at this link: SSC CGL

FAQs on Introduction to Statistics

1. What is the purpose of descriptive statistics?
Descriptive statistics is used to summarize and describe the main features of a dataset. It helps in organizing and presenting data in a meaningful way, such as through measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation). Descriptive statistics provide a snapshot of the data and allow for easier interpretation and analysis.
2. What are measures of central tendency?
Measures of central tendency are statistical measures that represent the center or average of a dataset. The most commonly used measures of central tendency are the mean, median, and mode. The mean is the sum of all values divided by the number of values, the median is the middle value when the data is arranged in ascending or descending order, and the mode is the value that appears most frequently in the dataset.
3. How do measures of dispersion help in understanding data variability?
Measures of dispersion provide information about the spread or variability of data points in a dataset. They help in understanding how much the individual data points deviate from the central tendency. For example, the range gives the difference between the maximum and minimum values, while the variance and standard deviation provide a measure of the average deviation from the mean. Larger measures of dispersion indicate more variability in the data.
4. What is the difference between descriptive and inferential statistics?
Descriptive statistics involves summarizing and describing the main features of a dataset, while inferential statistics involves making inferences or generalizations about a population based on a sample. Descriptive statistics focuses on presenting and interpreting the data at hand, whereas inferential statistics uses probability theory to make predictions or draw conclusions about a larger population based on a smaller sample.
5. How are statistics useful in everyday life?
Statistics play a crucial role in everyday life by providing tools and techniques to make sense of data and make informed decisions. They are used in various fields such as business, economics, healthcare, social sciences, and sports. For example, statistics can be used to analyze market trends, evaluate the effectiveness of medical treatments, understand social patterns, and predict outcomes in sports. By using statistics, we can gain insights and make evidence-based decisions in our personal and professional lives.
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