# Chapter 1 Use Of Statistics In Data Science Class 10 Questions and Answers

1. Which is a more accurate measure of central tendency when there are outliers in the data set?

a) Mean

b) Median

2. Mean absolute deviation is an identifier of the variability of the data set. Is this a correct statement?

a) Yes

b) No

3. The mean absolute deviation is divided by coefficient of mean absolute deviation to calculate

a) Variance

b) Median

c) Arithmetic Mean

d) Coefficient of Variation

### Use Of Statistics In Data Science Class 10 Questions and Answers

4. In a manufacturing company, the number of employees in unit A is 40, the mean is Rs. 6400 and the number of employees in unit B is 30 with the mean of Rs. 5500 then the combined arithmetic mean is

a) 9500

b) 8000

c) 7014.29

d) 6014.29

5. The mean deviation about the mean for the following data:

5, 6, 7, 8, 6, 9, 13, 12, 15 is:

a) 1.5

b) 3.2

c) 2.89

d) 5

6. The arithmetic mean of the numerical values of the deviations of items from some average value is called the

a) Standard Deviation

b) Range

c) Quartile Deviation

d) Mean Deviation

## Standard Questions

1. Explain the different ways of subsetting data.

Subsetting refers to choosing specific elements of a bigger dataset. There are two primary methods:

i) Subsetting rows: Choosing particular rows or observations on the basis of certain criteria, such as filtering data to specific age groups.

ii) Column subsetting: Selecting particular columns or variables in the data set, for example, selecting just one of the “name” and “score” columns from a list of student records.

2. When should we use median over mean?

If data contains extremities (outliers) that could skew results, you should use the median. It represents the middle point that is unaffected by outliers. In the case of a group of incomes the median will be higher in the case of a small number of people with extreme high or low earnings because it is an accurate value.

3. What is Mean Absolute Deviation?

Mean Absolute Deviation (MAD) MAD is a measure for the variability of data. It determines the average distance between each data item and the average. It can help discern how distributed the data is. It is less affected by outliers than a standard deviation.

### Use Of Statistics In Data Science Class 10 Questions and Answers

4. What is a two way relative frequency table? How is it different from two way frequency table?

A two-way table of relative frequencies It displays the percentage of values in two variables categorical. In contrast to a two-way frequency table which shows proportions or percentages of each mix that make it easier to evaluate the distributions.

5. What are two way frequency table beneficial for?

Benefits of two-way frequency tables: It aids in identifying patterns and connections between categorical variables. For instance, it is helpful to study how grades of students relate to the length of their studies or how preferences differ by age group.

6. What is Standard Deviation?

Standard Deviation: It’s a measure of the dispersion or spread of data points within an array. A higher standard deviation indicates greater variation, while an extremely low number indicates that the data is near to the average.

7. How to calculate Standard Deviation?

Calculating Standard Deviation

A) Calculate the average for the numbers.

B) Each time you have data points subtract the mean, then divide the result by.

C) Find the sum of all the squared differences.

D) Find your square root from the mean to calculate what is called the standard deviation.

### Use Of Statistics In Data Science Class 10 Questions and Answers

8. Name five real-life applications of Standard Deviation

Real-world applications of Standard Deviation:

i) Financial: This can help to assess the risk involved with investing.

ii) Quality Control: To assure consistency and the quality of the products.

iii) Medical: To study the effectiveness of treatments as well as variations in the patient’s response.

iv) Climate Science: To investigate the effects of temperature variations as well as weather patterns.

v) Learning: To analyze the performance of students and assess the effectiveness of the teaching method.

9. Explain five real-life situations where subsetting data can be advantageous.

The advantages of subsetting data when it comes to real-world scenarios:

i) Consumer Surveys analyzing certain segments of customers to learn about their preferences more clearly.

ii) Study of Health Concentrating on certain demographics or groups of people to find health risk factors.

iii) Marketing: Seizing advertising on specific regions according to consumer behaviour.

iv) Sport Analysis: Comparing the performance of players in particular games.

v) Social Science: Studying particular social groups to conduct research into attitudes and behaviors.