Tag: NTI

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

Distinguish between parametric and non-parametric test

Distinguish between parametric and non-parametric test   Parametric and non-parametric tests are two different categories of statistical tests used to analyze data. Here’s how they differ: Parametric Tests: 1. Assumption: Parametric tests assume that the data follows a specific distribution, usually the normal distribution. This assumption is crucial for accurate results. 2. Measurement Level: Parametric

Explain the difference between simple correlation and multiple correlation Simple and multiple correlations are two classifications of correlation. However, Correlation is simple if it concerns relationship between two variables while it is multiple if it concerns the relationship among three or more variables.

Explain the difference between simple correlation and multiple correlation. Simple and multiple correlations are two classifications of correlation. However, Correlation is simple if it concerns relationship between two variables while it is multiple if it concerns the relationship among three or more variables. Explain four (4) levels of measurement and give one (1) example each