The topic Use of Statistics in Data Science in Class 10 NCERT Solutions helps students understand how data is collected, organized, analyzed, and interpreted to make informed decisions. Statistics plays a crucial role in Data Science as it provides the foundation for data analysis, probability, and prediction.
Use of Statistics in Data Science Class 10 NCERT Solutions
Objective-Type Questions
Q. We want to get the cars of red colour from the below data set. Which type of subsetting should be used?
a) Column-based subsetting
b) Data-based subsetting
c) Row-based subsetting
d) None of the above
Q. Which is a more accurate measure of central tendency when there are outliers in the data set?
a) Mean
b) Median
Q. Mean absolute deviation is an identifier of the variability of the data set. Is this a correct statement?
a) Yes
b) No
Q. The mean absolute deviation is divided by the coefficient of mean absolute deviation to calculate
a) Variance
b) Median
c) Arithmetic Mean
d) Coefficient of Variation
Q. 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
Q. The mean deviation about the mean for the following data:
5, 6, 7, 8, 6, 9, 13, 12, and 15 are:
a) 1.5
b) 3.2
c) 2.89
d) 5
Q. 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
Q. Explain the different ways of subsetting data.
Answer: Subsetting means taking a small part from the big dataset. We use only those data which are required. This helps us to focus, save time and make analysis easier. Types of subsetting are:
- Row-Based Subsetting: Suppose one student table is there and you want to choose a specific row from the table; that is known as row-based subsetting.
- Column-Based Subsetting: In the table, if you want to choose specific columns, that is known as column-based subsetting.
- Data-Based Subsetting: In the table, if you want to choose rows based on specific data or conditions, this is known as data-based subsetting.
Q. When should we use median over mean?
Answer: So mean and median are both used to find the centre of a data set, but median is a more accurate form of central tendency, especially in scenarios where there are some irregular values, also known as outliers.
Q. What is Mean Absolute Deviation?
Answer: Mean Absolute Deviation helps to measure how spread out the data is. It tells us the average distance between each data point and the mean of the data. The formula for mean absolute deviation is:
MAD = (Sum of all absolute differences from the mean) / (Number of data points)
Q. What is a two-way relative frequency table? How is it different from a two-way frequency table?
Answer: A two-way frequency table is a chart that shows how two different categories of data are related to each other. It also helps us to count how many times each combination of categories appears. A two-way relative frequency table is similar to a two-way frequency table; the only difference is the two-way frequency table shows the counts, and the relative frequency table shows the percentages.
Q. What are two-way frequency tables beneficial for?
Answer: The benefits of a two-way frequency table are:
- Compare two categories.
- To understand the pattern
- Make data easier to read.
- Prepare a graph like a bar chart or segmented graph.
Q. What is Standard Deviation?
Answer: The standard deviation is the measure of how spread out the numbers are. To be specific, standard deviation represents how much the data is spread out around the mean or an average. For example, are all the points close to the average? Or are there lots of points way above or below the average?
Q. How to calculate standard deviation?
Answer: To calculate the standard deviation:
- Calculate the mean by adding up all the data pieces and dividing it by the number of pieces of the data.
- Subtract the mean from every value.
- Square each of the differences.
- Find the average of squared numbers calculated in point number 3 to find the variance.
- Lastly, find the square root of variance. That is the standard deviation.
Q. Name five real-life applications of standard deviation.
Answer: The five real-life applications of standard deviation are:
- Compare student performance in education.
- Measure risk in stock prices.
- Monitor product quality.
- Analyse player performance.
- Study temperatur changes over time.temperature
Q. Explain five real-life situations where subsetting data can be advantageous.
Answer: The five real-life situations where substituting data can be used are:
- School Survey
- Medical Study
- Sales Report
- Website Analytics
- Exam Results
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