Worksheet Solutions: Organisation of Data -1 | Economics Class 11 - Commerce PDF Download

Multiple Choice Questions

Q1:. Which of the following is/are objectives of classification?
(a) To simplify facts
(b) To facilitate comparison
(c) To point out similarities and dissimilarities
(d) All of the above
Ans: d

Q2: Raw data is made comprehensible by :
(a) collection of data
(b) classification of data
(c) organization of data
(d) presentation of data
Ans: b

Q3: In a frequency distribution, the class may be :
(a) singular or plural
(b) subjective or objective
(c) individual or discrete
(d) inclusive or exclusive
Ans: d

Q4: The characteristic of fact that can be measured in the form of numbers is called:
(a) Frequency
(b) variable
(c) attribute
(d) none of these
Ans: d

Q5: A refers to quantity whose value varies from one investigation to another.
(a) constant
(b) variable
(c) array
(d) none of these
Ans: b

Q6: Classification done according to the attributes of data.
(a) Quantitative Classification
(b) Qualitative classification
(c) Chronological classification
(d) Spatial classification
Ans: b

Q7: Formula for finding mid-value is given by
(a) l2-l2
(b) l2-l1/2
(c) l1-l2
(d) l1-l2/2
Ans: b

Q8: The frequency distribution of two variables is known as:
(a) Univariate distribution
(b) Bivariate distribution
(c) Multivariate
(d) None of the above
Ans: b

Q9: A given characteristics or attributes of a statistical enquiry refers to which of the following?
(a) Qualitative behavior
(b) Quantitative behavior
(c) Both (a) and (b)
(d) None of the above
Ans: a

Q10: A variable which can take integral as well as fractional values is known as ____.
(a) discrete variable
(b) continuous variable
(c) constant variable
(d) All of the above
Ans: b

Q11: Classification should be elastic in nature. Choose from the options below.
(a) True
(b) False
(c) Partially true
(d) Incomplete statement
Ans: a

Q12: Choose the correct equation from given below.
(Here S = Size of class, r = Range, n = Number of class)
(a) S = r/n
(b) S = r – n
(c) S = r + n
(d) None of these
Ans: a

Q13: A quantity which varies from one individual to another is known as ……… .
(a) Array
(b) Series
(c) Variable
(d) None of these
Ans: c

Q14: Which of the following is/are type(s) of classification?
(a) Chronological classification
(b) Geographical classification
(c) Qualitative classification
(d) All of the above
Ans: d

Q15: Food habits of an individual is an example of
(a) attribute
(b) variable
(c) continuous variable
(d) None of these
Ans: a

Q16: Classification of data based on time period is known as ____
(a) chronological classification
(b) geographical classification
(c) qualitative classification
(d) None of the above
Ans: a

Q17: Which of the following is/are statistical series based on construction?
(i) Individual series
(ii) Discrete series
(iii) Continuous series
Choose from the options below.
(a) (i) and (ii)
(b) (ii) and (iii)
(c) (i) and (iii)
(d) (i), (ii) and (iii)
Ans: b

Q18: The difference between highest and lowest items of the series is known as class width. Choose from the options below.
(a) True
(b) False
(c) Partially true
(d) Incomplete statement
Ans: b

Q19: Categorisation of data based upon the citizenship of an individual is an example of ____.
(a) quality
(b) attribute
(c) variable
(d) None of the above
Ans: b

Q20: Data which is grouped with reference to the attributes is referred to as ____.
(a) chronological classification
(b) geographical classification
(c) qualitative classification
(d) quantitative classification
Ans: c

Q20: Class width is same as ____.
(a) class frequency
(b) class interval
(c) Both (a) and (b)
(d) Neither (a) nor (b)
Ans: b

Q21: Mutually exclusive distribution is used to represent
(a) individual series
(b) discrete series
(c) continuous series
(d) All of these
Ans: c

Direction Read the following case study and answer questions on the basis of the same.
Collection of data is the first step in a statistical analysis. Data can be collected either from primary source or secondary source. Primary data is original as it is being collected for the first time. After collecting the data, next step is to organise the data as raw data cannot be used for further statistical analysis. There are various methods of classification of data based upon the nature of quantitative data.
Q22: Data are grouped with reference to the attributes is referred to as…classification.
(a) qualitative
(b) quantitative
(c) both (a) and (b)
(d) Neither (a) nor (b)
Ans: a

Q23: Time series graphs are presented on the basis of general characteristics of a data.
Choose from the options below.
(a) True
(b) False
(c) Partially true
(d) Incomplete statement
Ans: b

Q24: Assertion (A) Classification of data is done after organisation process.
Reason (R) Collection of raw data is not useful for further analysis.
Alternatives
(a) Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of Assertion (A)
(b) Both Assertion (A) and Reason (R) are true, but Reason (R) is not the correct explanation of Assertion (A)
(c) Assertion (A) is false, but Reason (R) is true
(d) Both are false
Ans: c

Q25: In which of the following method of frequency distribution, the upper limit of each class is excluded from the series but equal to the lower limit of the succeeding series?
(a) Continuous exclusive frequency distribution
(b) Continuous inclusive frequency distribution
(c) Continuous cumulative frequency distribution
(d) None of the above
Ans: a

Q26: Classification of data based on time period is known as ……… classification.
(a) chronological
(b) temporal
(c) spatial
(d) Both (a) and (b)
Ans: d

Long Answers

Q1: Define the following terms:-
Ans: Variable: A variable is a characteristic or quantity that can take different values in various observations. In statistical analysis, variables can be classified into two types: dependent and independent.
Attributes: Attributes are the specific qualities or characteristics of a variable. For example, if "height" is a variable, attributes might include "tall," "short," "average," etc.
Classification: Classification is the process of arranging data or objects into categories or groups based on their common characteristics or attributes.
Tabulation: Tabulation involves the systematic arrangement of data in the form of tables, making it easier to understand and analyze.
Statistical Series: A statistical series is a set of data arranged in a specific order or sequence, often for the purpose of analysis and presentation.
Frequency: Frequency refers to the number of times a particular value or category occurs in a dataset.
Class Frequency: Class frequency is the number of observations or data points that fall within a specific class or category in a frequency distribution.
Total Frequency: Total frequency is the sum of all the class frequencies in a frequency distribution.
Frequency Distribution: A frequency distribution is a table or graph that shows how data is distributed over various categories or intervals. It provides information about the frequency of each category or interval.
Class: In a frequency distribution, a class is a category or interval that represents a range of values. It is defined by its upper and lower limits.
Upper & Lower Limits: Upper limit is the highest value in a class, and the lower limit is the lowest value in that class. Together, they define the range of values for a class.
Class Interval: Class interval is the range between the upper and lower limits of a class in a frequency distribution.
Midpoint: The midpoint of a class interval is the middle value of that interval. It is calculated as the average of the upper and lower limits.

Q2: What are the different types of series on the basis of general characters?
Ans: On the basis of general characteristics, there are two types of series:
Qualitative Series: In qualitative series, data is classified based on non-numeric attributes or qualities. For example, classifying cars into categories like "sedan," "SUV," "hatchback," etc., is a qualitative series.
Quantitative Series: In quantitative series, data is classified based on numeric values or measurements. For example, grouping students' heights into intervals like "150-160 cm," "160-170 cm," etc., is a quantitative series.

Q3: What are the 3 types of series on the basis of construction?
Ans: On the basis of construction, there are three types of series:
Individual Series: In an individual series, each data point is listed separately. This type of series is suitable for a small dataset with unique values.
Discrete Series: In a discrete series, data is grouped into distinct and separate classes or intervals. It is used when data falls into distinct categories or ranges.
Continuous Series: In a continuous series, data is grouped into intervals where the upper limit of one interval is the same as the lower limit of the next. This type of series is used when data is continuous and can take any value within a range.

Q4: Define an array?
Ans: An array is a data structure that stores a collection of elements or values, each identified by an index or a key. In statistics, an array can be used to store a set of data values in a systematic manner. For example, an array can be used to store a list of exam scores for a group of students, with each score assigned to a specific position or index in the array.

Q5: Distinguish between
Ans: Discrete & continuous variable:
A discrete variable can only take on specific, distinct values (usually integers) and cannot take on values in between. For example, the number of students in a class is a discrete variable.
A continuous variable can take on any value within a given range and can include fractional or decimal values. For example, height or weight is a continuous variable.
Discrete & continuous series:
A discrete series is used when data can be categorized into separate, distinct classes or intervals. There are gaps or spaces between the classes.
A continuous series is used when data can take any value within a range, and there are no gaps or spaces between the classes.
Inclusive & Exclusive Method:
Inclusive method includes the lower limit of a class in one interval and the upper limit of the same class in the next interval. There is no overlap between adjacent classes.
Exclusive method excludes the upper limit of a class in one interval and the lower limit of the same class in the next interval. There is overlap between adjacent classes.
Simple & Cumulative series:
Simple series presents the frequency distribution of individual classes separately.
Cumulative series presents the cumulative frequency distribution, which adds up the frequencies as you move through the classes.

Q6: Give the steps of Construction:-
Ans: Discrete frequency distribution:
Data Collection: Collect the raw data that you want to create a frequency distribution for.
Data Sorting: Sort the data in ascending or descending order to facilitate the grouping process.
Class Formation: Decide on the number of classes (intervals) you want to create. Choose appropriate class intervals.
Tallying: Count the number of data points that fall within each class interval and record the frequencies.
Tabulation: Create a table that includes columns for class intervals, class boundaries, frequencies, and cumulative frequencies.
Graphical Representation: Optionally, you can create a histogram or bar graph to visualize the frequency distribution.
Continuous frequency distribution: The steps for constructing a continuous frequency distribution are similar to those for a discrete frequency distribution, with the main difference being that class intervals in a continuous distribution have no gaps or overlaps. Here are the steps:
Data Collection: Collect the raw data.
Data Sorting: Sort the data.
Class Formation: Decide on the number of classes and appropriate class intervals. Ensure that class intervals have no gaps or overlaps.
Tallying: Count the number of data points that fall within each class interval.
Tabulation: Create a table with columns for class intervals, class boundaries, frequencies, and cumulative frequencies.
Graphical Representation: Optionally, create a histogram or frequency polygon for visualization.

Q7: Give the 7 principles of grouping data.
Ans: The seven principles of grouping data for effective statistical analysis are as follows:
Mutually Exclusive: Each data point should belong to only one category or class. There should be no overlap or ambiguity in classification.
Collective Exhaustive: All data points should be included in the classification. There should be no data left unclassified.
Clear and Understandable Categories: The categories or classes should be well-defined and easy to understand, ensuring clarity in classification.
Non-overlapping Intervals: In the case of continuous data, class intervals should not overlap to avoid confusion.
Equal Class Intervals: In many cases, it's beneficial to have equal class intervals to simplify.