MCQs from Statistical Inference covering the topics of Estimation and Hypothesis Testing for the preparation of exams and different statistical job tests in Government/ Semi-Government or Private Organization sectors. This Estimation online quiz will also help get admission to different colleges and Universities. The Estimation Online Quiz will help the learner to understand the related concepts and enhance their knowledge.
Estimation Online Quiz with Answers
| MCQs Estimation 08 | MCQs Estimation 07 | |
| MCQs Estimation 06 | MCQs Estimation 05 | MCQs Estimation 04 |
| MCQs Estimation 03 | MCQs Estimation 02 | MCQs Estimation 01 |
Statistical inference is a branch of statistics in which we conclude (make wise decisions) about the population parameter by making use of sample information. To draw wise decisions, one can use estimation and hypothesis testing techniques based on extracted information from descriptive statistics. Statistical inference can be further divided into the Estimation of parameters and testing of the hypothesis.
Statistical estimation is the foundation of learning about a population by analyzing a sample. It’s essentially making educated guesses about population characteristics (parameters) based on the data we collect (samples).
Estimation is a way of finding the unknown value of the population parameter from the sample information by using an estimator (a statistical formula) to estimate the parameter. One can estimate the population parameter by using two approaches (I) Point Estimation and (ii) Interval Estimation.
In point Estimation, a single numerical value is computed for each parameter, while in interval estimation a set of values (interval) for the parameter is constructed. The width of the confidence interval depends on the sample size and confidence coefficient. However, it can be decreased by increasing the sample size. The estimator is a formula used to estimate the population parameter by making use of sample information.
There are various techniques for statistical estimation that depends on the type of data and parameter of interest begin estimated. The followings are few techniques for statistical estimation:
- Mean Estimation: Sample mean is used to estimate the population mean for continuous data.
- Proportion Estimation: Sample proportion is used to estimate the population proportion for categorical data (e.g., yes/ no response).
- Regression Analysis: Used to estimate relationships between variables and make predictions about a dependent variable based on an independent variable.
Statistical estimation is a powerful tool that allows us to:
- Move beyond the sample: Make generalizations about the population from which the data came.
- Quantify uncertainty: Acknowledge the inherent variability in using samples and express the margin of error in the estimates.
- Guide decision-making: Inform choices based on the best available information about the population.
