Explanation

• Control charts and procedures of descriptive statistics used to enhance a process are classified as Statistical Process Control (SPC) tools.
• SPC is a methodology that uses statistical techniques to monitor and control processes to ensure they operate within predetermined limits.

Explanation

The product of the first 'n' natural numbers is represented by the formula:

n! (n factorial) = 1 × 2 × 3 × ... × (n-2) × (n-1) × n

This is denoted by the symbol "n!" and is read as "n factorial".

Explanation

• Regression analysis is a statistical technique used to establish a relationship between two variables (independent and dependent) to predict the value of one variable based on the other.
• It helps in building a prediction model that can forecast the outcome.

Explanation

• The alternate hypothesis is also known as the alternative hypothesis.
• It determines whether a test is one-tailed or two-tailed.

Explanation

• If heteroscedasticity is present in a regression model but ignored, the Ordinary Least Squares (OLS) estimator will still be unbiased, but it will not be efficient.
• This means that the estimator will not have the smallest possible variance, and the estimates may not be precise.

Explanation

• When several unbiased samples are drawn from the same population, the sampling technique is Random Sampling.
• In random sampling, each member of the population has an equal chance of being selected, and the samples are drawn independently.
• This allows for the calculation of sampling distributions and the estimation of population parameters.

Explanation

Probability refers to the likelihood of a single event or outcome occurring, not a collection of experiments.

Explanation

• A Type-II error means accepting an incorrect hypothesis (or failing to reject a false null hypothesis).
• This means that the test or experiment has failed to detect a significant effect or difference when it actually exists.

Explanation

Since X is a uniform variate between 0 and 3, the probability density function (pdf) of X is:

f(x) = 1/3 for 0 ≤ x ≤ 3

To find E(X²), we need to calculate the expected value of X², which is:

E(X²) = ∫x²f(x)dx = ∫(x²/3)dx from 0 to 3

Evaluating the integral, we get:

E(X²) = (1/3)∫x²dx from 0 to 3 = (1/3)[(3³)/3] = 3

So, the expected value of X² is 3.

Explanation

• The Second Quartile (Q2) is a measure of central tendency, also known as the median.
• It is the middle value of a dataset when it is sorted in order.