Greetings, class. Today, we will delve into the realm of education and explore potential problem areas that warrant investigation. These problem areas often have a substantial impact on the quality of education. Let’s break down the key issues and provide examples for each: A. Inadequate Funding: Insufficient financial support can hinder educational institutions in various
1. (a) What is educational statistics? (b) Explain any five (5) purposes for its use in Nigeria’s educational system. (a) Educational Statistics: Educational statistics refers to the application of statistical methods and techniques to gather, analyze, interpret, and present data related to various aspects of education. It involves the systematic collection and analysis of
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. 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
Using a scatter diagram differentiate between negative, positive and zero correlation. A negative correlation refers to a relationship where the variables move in opposite direction i.c. an increase in one variable is accompanied by a decrease in another variable. For example, an increase in visits to the pub is accompanied by a decrease in exam
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
(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.
(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
1. (a) Describe sampling (b) Explain any four (4) of its significance 2. (a) Distinguish between Type I and Type II error (b) Define Kurtosis (c) With the aid of diagram, explain the following: i. Leptokurtic ii. Platykurtic iii. Mesokurtic 3. (a) What is population of a study? (b) Explain the following sampling techniques
When rolling a fair six-sided die 🎲, there are three outcomes that result in a multiple of 2: 2, 4, and 6. Since there are a total of six equally likely outcomes (numbers 1 through 6) when rolling a standard die, the probability of obtaining a multiple of 2 is the ratio of favorable outcomes
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
