STATISTICS-True/False

Statistics in Class 10 introduces students to organised ways of handling real-life data using concepts like mean, median, mode, and graphical representations such as histograms and ogives. To help consolidate these ideas, the following True and False questionnaire focuses on definitions, formulas, and conceptual understanding from NCERT Mathematics Chapter 13 “Statistics”. Each statement is followed by an answer and a brief explanation so that learners can quickly check their understanding, correct misconceptions, and strengthen their preparation for school tests and board examinations.

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STATISTICS

by Academia Aeternum

1. Statistics is a branch of mathematics that deals with the collection, organisation, analysis and interpretation of data.
2. In Class X, statistics deals only with ungrouped (raw) data and does not consider grouped data.
3. A frequency distribution table shows each observation together with the number of times it occurs.
4. For continuous grouped data, class intervals in a frequency distribution must not overlap.
5. The sum of the frequencies in a grouped frequency distribution is equal to the total number of observations.
6. The mean of a set of observations is always one of the given observations.
7. For grouped data, the mean can be calculated using the assumed mean method to simplify calculations.
8. In a grouped frequency distribution, the mean is computed using the mid-point of each class interval.
9. The median of a data set is the arithmetic average of all observations.
10. For ungrouped data, if the number of observations is odd, the median is the \(\frac{n+1}{2}\)th observation in the ordered list.
11. For grouped data, the median always coincides with the mid-point of the median class.
12. To find the median of grouped data, the class whose cumulative frequency is just greater than \(\frac{n}{2}\) is taken as the median class.
13. The mode of a data set is the value that occurs most frequently.
14. In a grouped frequency distribution, the modal class is the class interval with the smallest class width.
15. For grouped data, the mode can be estimated using a formula involving the frequencies of the modal class and its neighbouring classes.
16. A data set can have more than one mode.
17. In the context of this chapter, cumulative frequency is obtained by successively adding frequencies down the table.
18. A “less than” cumulative frequency curve (ogive) is drawn by plotting upper class boundaries against their corresponding cumulative frequencies.
19. The point of intersection of “less than” and “more than” ogives gives a graphical estimate of the mean.
20. In many real-life distributions treated in this chapter, mean, median and mode need not have the same value.
21. For grouped data in Class X, the relationship \(\text{Mode} = 3 \times \text{Median} - 2 \times \text{Mean}\) may be used under certain conditions.
22. When data are given in grouped form, the exact original observations can be uniquely recovered from the frequency distribution table.
23. In a frequency distribution, if all observations have the same value, then mean, median and mode are equal.
24. While drawing a histogram for continuous data, the area of each rectangle is proportional to the frequency of the corresponding class.
25. For grouped data with equal class intervals, choosing different origins (assumed means) changes the actual value of the mean.

Frequently Asked Questions

Statistics is the branch of mathematics that deals with the collection, organisation, presentation, analysis, and interpretation of numerical data.

Statistics helps in understanding trends, making comparisons, predicting outcomes, and taking data-based decisions in real-life situations.

Data refers to numerical information collected from observations, surveys, or experiments for analysis.

Raw data is unorganised data collected directly from a source without any classification or arrangement.

Grouped data is data organised into class intervals to simplify analysis when observations are large in number.

It is a table that shows how often values occur within defined class intervals.

Class intervals are divisions of data into fixed ranges used to group observations.

Class width is the difference between the upper and lower limits of a class interval.

The class mark is the midpoint of a class interval, calculated as \((\text{upper limit} + \text{lower limit})/2\).

Measures of central tendency describe a central or typical value of data, such as mean, median, and mode.

Mean is the average value of grouped data calculated using class marks and frequencies.

\(\bar{x} = \frac{\sum f_i x_i}{\sum f_i}\), where \(x_i\) are class marks and \(f_i\) are frequencies.

It is a method to calculate mean by assuming a convenient value as the mean to simplify calculations.

A short-cut method of finding mean using deviations divided by class width to reduce computation.

It is preferred when class intervals are equal and numbers are large.

Median is the value that divides the data into two equal parts when arranged in order.

The class interval that contains the median value.

\(\text{Median} = l + \left(\frac{\frac{N}{2} - cf}{f}\right)h\)

\(l\): lower limit, \(N\): total frequency, \(cf\): cumulative frequency before median class, \(f\): frequency, \(h\): class width

Mode is the value that occurs most frequently in a data set.

The class interval with the highest frequency.

\(\text{Mode} = l + \left(\frac{f_1 - f_0}{2f_1 - f_0 - f_2}\right)h\)

\(f_1\) is modal class frequency, \(f_0\) preceding frequency, \(f_2\) succeeding frequency.

It is the running total of frequencies in a distribution.

A graphical representation of cumulative frequencies, also called an ogive.

An ogive formed using cumulative frequencies less than the upper class limits.

An ogive drawn using cumulative frequencies greater than the lower class limits.

By plotting both ogives and locating the x-coordinate of their intersection.

They summarise large data sets using a single representative value.

Mean is best for symmetrical distributions.

Median is preferred for skewed distributions.

When identifying the most common value, such as shoe size or popular choice.

Economics, science, medicine, education, population studies, and business analysis.

To analyse results, performance trends, and assessment outcomes.

Numerical problems, formula-based questions, graphical interpretation, and case-study questions.

Errors in tables lead to incorrect calculations and wrong conclusions.

Wrong class marks, incorrect cumulative frequencies, and formula substitution errors.

All major steps with formulas must be clearly shown for full marks.

Yes, for a perfectly symmetrical distribution.

Changing the origin and scale using assumed mean and step deviation.

Drawing conclusions and inferences from analysed data.

Analytical thinking, logical reasoning, and numerical accuracy.

Yes, due to formula-based questions and structured solutions.

Memorise formulas, practice numericals, and avoid calculation mistakes.

It carries significant weightage in the Class X Mathematics examination.

Proper scale, labeling, and accuracy are essential for full marks.

Frequency per unit class width, used in unequal class intervals.

Yes, they help compare distributions visually.

Displaying data using tables, graphs, and curves.

It teaches how data can be analysed logically to draw meaningful conclusions.

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