Psychological Statistics : Lesson 1

Digital flashcard reviewer for lesson 1 : Variability and Covariance

Variability

supporting details: It refers to how spread out the scores are in a data set. It describes how much the scores differ from each other and from the central tendency (such as the mean or median). It allows researchers to see how much individual differences there are in a population. For example, a researcher might be interested in studying the variability of anxiety scores in a group of students. If the anxiety scores are highly variable, it suggests that there is a wide range of anxiety levels among the students. This information could be useful for developing targeted interventions for anxiety.

This is the degree to which the scores deviate from the mean or the amount of spread of the scores around the mean.

Covariance

supporting details: Covariance is a measure that goes beyond just looking at how spread out individual variables are (like variability) and dives into how two variables change together. It tells you whether two variables tend to move in the same direction (positive covariance), opposite directions (negative covariance), or have no relationship at all (zero covariance).

A statistical technique called _______ is used to ascertain the relationship between the two random variables' motions or movement.

True

supporting details: In hypothesis testing and inferential statistics, our primary goal is to carefully analyze data patterns, apply rigorous methods, and draw reliable conclusions that are free from random variability, in order to gain a deeper understanding of the relationships between variables and establish meaningful insights.

True or False

Our objective in hypothesis testing and inferential statistics is to identify methodical explanations for distinctions and eliminate chance as a contributing factor.

Correlation

supporting details: Correlation is a powerful tool in psychology statistics for uncovering how two variables are linearly related, providing valuable insights into potential connections between psychological characteristics.

A statistics metric called ________

It describes how two or more variables are related, both in terms of magnitude and direction. It is also a statistical measure that expresses the extent to which two variables are linearly related.

True

supporting details: Covariance is a fundamental statistical concept that represents the relationship between two variables, emphasizing how they change collectively rather than individually. The prefix "co-" denotes the collaborative nature of these variations, highlighting not only the individual fluctuations but also focusing on how these variations harmonize and occur simultaneously, providing deeper insights into the intricate dynamics of quantitative data analysis.

True or False

Covariance is the idea that variables vary jointly (the prefix co- meaning "collectively"). The prefix "co-" signifies that it's not just about individual variations but how these variations co-occur or happen together.

True

explanation for the answer:

While a correlation between variables may suggest a relationship or association, it is important to note that correlation does not imply causation. In other words, just because two variables are correlated, it does not necessarily mean that changes in one variable directly cause changes in the other variable. There could be other underlying factors or variables at play that influence the relationship between the two variables. Therefore, it is essential to conduct further research and analysis to determine the true nature of the relationship between the variables.

True or False?

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable.

True

explanation for the answer:

The table for sum of products is a helpful visual representation that breaks down the total variation in a set of data into three components: the variation explained by the independent variable X, the variation explained by the independent variable Y, and the variation explained by the interaction between X and Y. This table is created by calculating the sum of squares for X and Y separately, and then adding a final column that represents the products of X and Y. This allows for a more comprehensive analysis of the relationship between the two variables and provides insight into how they interact with each other.

True or False?

The table for sum of products is simply a sum of squares table for X, plus a sum of squares table for Y, with a final column of products.