Distributions in Data Science is an important topic in Class 10 NCERT Data Science (Subject Code 417/419). A distribution shows how data values are spread or arranged. By studying distributions, students learn to organize data in frequency tables, histograms, and graphs, making it easier to analyze and interpret patterns.
Distributions in Data Science Class 10 NCERT Solutions
Please choose the correct option in the questions below.
Q. If a card is chosen from a standard deck of cards, what is the probability of getting a five or a seven?
a) 4/52
b) 1/26
c) 8/52
d) 1/169
Q. Which of the following is the condition for uniform distribution?
a) Each value in the set of possible values has the exact same possibility of happening.
b) Have a constant probability of success
c) Has only two possible outcomes
d) Must have at least 3 trials
Q. The collection of one or more outcomes from an experiment is called
a) Probability
b) Distribution
c) Event
d) Random Experiment
Q. Which of the following are types of distributions?
a) Continuous
b) Discrete
c) Both of them
Q. Which of the following is not an example of discrete probability distribution?
a) The sale or purchase price of a house
b) The number of bedrooms in a house
c) The number of bathrooms in a house
d) Whether or not a home has a swimming pool in it
Q. A discrete probability distribution may be represented by
a) A table
b) A graph
c) A Mathematical Equation
d) All of these
Q. What is the probability that a ball is drawn at random from a jar?
a) 0.1
b) 1
c) 0.5
d) 0
e) Cannot be determined from given information
Q. The statistical investigative process has which of the following components:
a) Formulate Statistical Investigative Questions
b) Collect/Consider the Data
c) Analyze the Data
d) Interpret the Data
e) All of the above
Standard Questions
Q. Explain what distribution in data science is with the help of two examples.
Answer: The distribution in data science helps to identify the way values of a variable are spread or arranged. It helps to understand patterns, tendencies, and probabilities in data. For example,
- Normal distribution: In normal distribution a bell-shaped curve is there, and most values cluster around the mean. For example, human height, where most people are of average height, with fewer being very short or very tall.
- Uniform distribution: In uniform distribution each and every one gets a chance. For example, rolling a fair die every time, a number will come from 1 to 6 and has a 1/6 chance of appearing.
Q. Explain what a statistical problem-solving process is.
Answer: The statistical problem-solving process is a step method used to solve real-world problems using data. This process helps to make informed decisions by collecting, analyzing, and interpreting data.
The steps in the process are:
- Formulate a Statistical Question
- Collected or Considered data
- Analyze the data.
- Interpret the results.
Q. Explain how distributions are broadly categorized. Support your answer with appropriate examples for each category.
Answer: The distributions in statistics are broadly categorized into two types: discrete and continuous.
- Discrete Distributions: Discrete data is the data that takes only specified values. For example, if you give a test, you can either pass or fail. So, data is discrete in this case, as it has only two specified outcomes.
- Continuous Distributions: Continuous data is the data that can take any value within a given range. This range can be either finite or infinite. For example, the depth of an ocean, the weight of a person, or the length of a road.
Q. Explain in detail how we formulate statistical investigative questions.
Answer: A statistical investigative question is a smart question that has different answers. It helps to study a group of things and find the patterns within it. For example, if we ask, “Do plants grow faster with more sunlight?” the following are all statistical investigative questions that anticipate variability and can lead to a rich data collection process and subsequent analysis of the data.
Q. Name five instances where you have observed a uniform distribution.
Answer: The five instances where we have observed a uniform distribution are
- Rolling a fair die
- Drawing a Card from a shuffled Deck
- Randomly choosing a day of the week
- Spinning a fir wheel (like a board game)
- Generating a random number between 1 and 10
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