Exploring Data Science Concepts

What is the definition of mean in statistics?

• The mean is the difference between the highest and lowest numbers.

• The mean is the average of a set of numbers.

• The mean is the sum of all numbers in a set without dividing by the count.

• The mean is the most frequently occurring number in a set.

How do you calculate the percentile of a data set?

• Arrange data in ascending order and use the formula: Percentile = (P/100) * (N + 1).

• Count the number of data points and divide by two.

• Use the formula: Percentile = (N/100) * P.

• Calculate the average of the data set.

What is the formula for standard deviation?

• σ = (Σ(xi - μ)²) / N

• σ = √(Σ(xi - μ)² / N)

• σ = Σ(xi - μ) / N

• σ = √(Σ(xi + μ)² / N)

Explain the concept of coefficient of variation.

• The coefficient of variation is the same as the standard deviation.

• The coefficient of variation is a measure of relative variability, calculated as (Standard Deviation / Mean) * 100.

• The coefficient of variation is calculated as Mean / Standard Deviation.

• The coefficient of variation measures absolute variability without reference to the mean.

What does a correlation coefficient of 1 indicate?

• A perfect positive linear relationship.

• A perfect negative linear relationship.

• No relationship at all.

• A weak positive linear relationship.

What does a correlation coefficient of -1 indicate?

• No relationship at all.

• A perfect positive linear relationship.

• A weak negative linear relationship.

• A perfect negative linear relationship.

How can you interpret a positive correlation between two variables?

• A positive correlation means that both variables increase together.

• A positive correlation means that one variable decreases while the other increases.

• A positive correlation indicates that the variables are unrelated.

• A positive correlation suggests that both variables fluctuate randomly.

What is the difference between descriptive and inferential statistics?

• Descriptive statistics are used for qualitative data; inferential statistics are used for quantitative data.

• Descriptive statistics analyze data; inferential statistics collect data.

• Descriptive statistics predict future trends; inferential statistics summarize data.

• Descriptive statistics summarize data; inferential statistics make predictions about a population based on a sample.

How do you find the median of a data set?

• Arrange the data in order and find the middle value or average of the two middle values.

• Select the largest number in the data set.

• Add all the numbers and divide by the total count.

• Choose the first number in the ordered list.

What is the significance of the interquartile range?

• It represents the highest and lowest values in the dataset.

• It measures the total range of a dataset.

• The interquartile range is significant because it indicates the variability of the central portion of a dataset, helping to identify outliers and understand data distribution.

• It is used to calculate the mean of the dataset.