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Page 1 CPT Section D Quantitative Aptitude Chapter 10 Dr. R. B. Tiwari Page 2 CPT Section D Quantitative Aptitude Chapter 10 Dr. R. B. Tiwari Question Time Page 3 CPT Section D Quantitative Aptitude Chapter 10 Dr. R. B. Tiwari Question Time a) Economics b) Business Management c) Commerce and Industry d) Always Answer: (d) always Page 4 CPT Section D Quantitative Aptitude Chapter 10 Dr. R. B. Tiwari Question Time a) Economics b) Business Management c) Commerce and Industry d) Always Answer: (d) always (a) A qualitative characteristics (b) A Quantitative Characteristics (c) A Measurable Characteristics (d) All These Answer: (a) A qualitative characteristics Page 5 CPT Section D Quantitative Aptitude Chapter 10 Dr. R. B. Tiwari Question Time a) Economics b) Business Management c) Commerce and Industry d) Always Answer: (d) always (a) A qualitative characteristics (b) A Quantitative Characteristics (c) A Measurable Characteristics (d) All These Answer: (a) A qualitative characteristics (a) An attribute (b) A discrete variable (c) A continuous variable (d) (b) or (c) Answer: (b) A discrete variableRead More
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FAQs on MCQ - Statistical Description of Data - Quantitative Aptitude for CA Foundation
| 1. What is statistical description of data? |  |
Ans. Statistical description of data refers to the process of summarizing and analyzing data using statistical methods. It involves organizing and presenting data in a meaningful way to understand its characteristics, patterns, and trends.
| 2. Why is statistical description of data important? | |
Ans. Statistical description of data is important because it helps in making informed decisions based on data analysis. It provides insights into the data, helps in identifying patterns and trends, and allows for comparisons between different groups or variables. It also helps in understanding the variability and distribution of data.
| 3. What are the different measures of central tendency used in statistical description of data? | |
Ans. The measures of central tendency used in statistical description of data are:
- Mean: It is the average value and is calculated by summing up all the values and dividing it by the total number of values.
- Median: It is the middle value of a data set when arranged in ascending or descending order. It divides the data into two equal halves.
- Mode: It is the value that occurs most frequently in a data set.
| 4. How are measures of dispersion useful in statistical description of data? | |
Ans. Measures of dispersion are useful in statistical description of data as they provide information about the spread or variability of the data. They help in understanding how the data points are distributed around the measures of central tendency. Some commonly used measures of dispersion are range, variance, and standard deviation.
| 5. What is the difference between descriptive statistics and inferential statistics in statistical description of data? | |
Ans. Descriptive statistics involves summarizing and describing data using measures such as mean, median, mode, and measures of dispersion. It focuses on describing the characteristics of the data set.
In contrast, inferential statistics involves making inferences or drawing conclusions about a population based on a sample. It uses probability theory and hypothesis testing to make predictions or generalizations about the population using sample data.
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