Sampling is the process of selecting a subset from a population to estimate population characteristics. Standard error measures the variability of a sample statistic from the population parameter. Smaller standard error indicates more accurate estimates. Both are crucial in psychological research for drawing valid inferences from data.
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The normal curve, also called the bell curve, represents a symmetrical distribution of data where most values cluster around the mean. It is essential in psychology as many traits follow a normal distribution. Properties include equal mean, median, and mode, and predictable data spread governed by standard deviation.
Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. In simple linear regression, the relationship is modeled using a straight line (y = a + bx). It helps in prediction and identifying how variables are related in psychological research.
The direction of correlation indicates the type of relationship between two variables. A positive correlation means both variables increase together, while a negative correlation means one increases as the other decreases. Zero correlation indicates no relationship. This concept is crucial in psychological research to understand associations between behaviors or traits.
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Decision errors occur in hypothesis testing when incorrect conclusions are drawn. There are two types: Type I error, where a true null hypothesis is wrongly rejected, and Type II error, where a false null hypothesis is not rejected. These errors affect the reliability of research, and their likelihood is influenced by sample size, effect size,
Point estimation refers to the process of using sample data to estimate a single value (point) as an approximate value of a population parameter. Common point estimators include the sample mean for population mean, and sample proportion for population proportion. While efficient and easy to interpret, point estimates may lack accuracy if not supported by
The sign test is a non-parametric statistical test used to evaluate the median difference between paired observations or a sample median. It is particularly useful when the assumptions of parametric tests (like normality) are violated. The test only considers the direction of change (positive or negative), not the magnitude, making it simple and robust for
Compute Chi-Square for Job Position and Work Motivation Scores Introduction The Chi-square (χ²) test is a non-parametric statistical method used to test the relationship between two categorical variables. It compares the observed frequencies in a contingency table with the expected frequencies that would occur if there were no relationship between the variables. In this question,
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Describe Point-Biserial Correlation and Phi Coefficient Introduction Correlation is a measure of the relationship between two variables. In psychological research, when dealing with specific types of variables—particularly dichotomous ones (variables that take only two values)—special correlation methods are used. Two such techniques are the point-biserial correlation and the phi coefficient. These are valuable tools when
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Using t-Test to Find Significant Difference in Achievement Motivation Scores Between Male and Female Students Introduction The t-test is a widely used parametric test in statistics for comparing the means of two independent groups. In psychology, it helps determine whether the differences in test scores, behaviors, or psychological traits between groups are statistically significant or
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