Distinguish clearly between type I and type II errors.

Distinguish clearly between type I and type II errors.   Tabular comparison of Type I and Type II errors: Error Type Type I Error Type II Error Definition Incorrectly rejecting a true Failing to reject a false null hypothesis (False Positive) null hypothesis (False Negative) Symbol α β Occurrence Occurs when there is no effect,

Explain the concept of significance level.

Explain the concept of significance level. Scientific conclusions are statements with high probability of being correct and not statements of absolute truth. Before we carry out the experiment, we must determine how high the probability will be in order to accept or reject a null hypothesis. We need to carry out a test of significance

Write briefly on the following terms A one tailed test, Systematic sampling, A two tailed test, Cluster sampling, Accidental / Haphazard Sampling

A one-tailed test: This type of statistical test involves making a directional prediction about the outcome. For instance, it could be predicted that students who engaged in micro-teaching will achieve higher scores in practical teaching compared to those who did not participate.   Systematic sampling: In this method of sampling, a sample is chosen by

2. (a) Explain educational statistics (b) Is statistics really needed in education? Discuss

(a) Educational statistics is the application of statistical methods to address issues related to various aspects of education. It involves organizing, summarizing, presenting, and interpreting data obtained from educational assessments. By employing educational statistics, we can measure the relationships between different educational variables, draw conclusions, and make predictions that aid in achieving specific educational objectives.

Average Mean or Arithmetic Mean

        (a) Define A. Mean B. Median C. Mode D. Standard deviation. (b) Find the mean and mode of the following set of data A. 2, 3, 5, 7, 9, 9, 10, 11, 14, 18 B. 3, 5, 8, 10, 12, 15, 16 . 2, 3, 4, 4, 5, 5,7,7,7,9    

Distinguish the difference between Type 1 and Type 2 errors

Type 1 and Type 2 errors are concepts related to hypothesis testing in statistics. Here’s how they differ: Type 1 Error (False Positive): 1. Occurs when: A Type 1 error happens when a null hypothesis that is actually true is incorrectly rejected. 2. Meaning: It’s a false positive, indicating that the test incorrectly indicates a

Define Discrete variable

A discrete variable is a type of quantitative variable in statistics that represents distinct, separate values or categories. It can only take on specific, distinct numerical values within a certain range, often as whole numbers. Discrete variables cannot have values between these distinct points, making them different from continuous variables which can take any value