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
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 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 four (4) levels of measurement and give one (1) example each
A. Nominal Scale: Nominal data are counted data. Each individual can only be a member of mutually exclusive category and not the other. All members of each category include notionally, gender, socioeconomic status, occupation, role, religious affiliation etc. Numbers are often used at the nominal level, but only in order to identify the categories. The
What is a scale of measurement? Scale of measurement entails the method used for translation of observation into numbers. For measurement to be carried out in statistics, objects and events has to be assigned numerals according to certain scales or rules. Starting with variables, some rules are then used to determine how these variables will
1. Random Sampling: Random sampling involves selecting a subset of individuals from the entire population in such a way that each member of the population has an equal chance of being chosen. This technique ensures that the sample is representative of the population, reducing the potential for bias. In educational research, a random sample
The steps are as follows: Calculate the mean (average) of the scores. Subtract the mean from each score, square the result. Calculate the mean of those squared differences. Take the square root of that mean to get the standard deviation. Step 1: The mean is indeed 5.5. Step 2: Subtract the mean from each
Write briefly on the following terms : (a) A one-tailed test. (b) Systematic Sampling (c) A Two-tailed test (d) Cluster sampling (e) accidental/ haphazard sampling (a) A One-Tailed Test: A one-tailed test, also known as a one-sided test, is a statistical hypothesis test that examines whether a sample’s result falls significantly above
Educational Statistics refer to the quantitative data that is collected, analyzed, and interpreted to gain insights into various aspects of the education system. These statistics play a pivotal role in shaping educational policies, improving teaching methodologies, and enhancing the overall quality of education. Key Aspects of Educational Statistics: Data Collection: Educational statistics involve
