Table of Contents
- 1 Can there be two quantitative variables?
- 2 What are 2 quantitative variables?
- 3 How do you compare two quantitative variables?
- 4 How would you describe the relationship between two quantitative variables?
- 5 What determines a strong correlation?
- 6 What statistical analysis is done to find how strong a relationship is between two quantitative variables?
- 7 Is there a linear relationship between two quantitative variables?
- 8 When is the correlation coefficient of bivariate data misleading?
Can there be two quantitative variables?
The outcome variable, also known as a dependent variable. A scatterplot can be used to display the relationship between the explanatory and response variables. A graphical representation of two quantitative variables in which the explanatory variable is on the x-axis and the response variable is on the y-axis.
What are 2 quantitative variables?
Quantitative Variables. As discussed in the section on variables in Chapter 1, quantitative variables are variables measured on a numeric scale. Height, weight, response time, subjective rating of pain, temperature, and score on an exam are all examples of quantitative variables.
Is a strong relationship between two variables?
The correlation between two variables is considered to be strong if the absolute value of r is greater than 0.75. However, the definition of a “strong” correlation can vary from one field to the next….What is Considered to Be a “Strong” Correlation?
| Absolute value of r | Strength of relationship |
|---|---|
| 0.5 < r < 0.75 | Moderate relationship |
| r > 0.75 | Strong relationship |
What is an example of two quantitative variables?
Examples of Quantitative Variables / Numeric Variables: High school Grade Point Average (e.g. 4.0, 3.2, 2.1). Number of pets owned (e.g. 1, 2, 4). Bank account balance (e.g. $100, $987, $-42. Number of stars in a galaxy (e.g. 100, 2301, 1 trillion) .
How do you compare two quantitative variables?
A scatterplot is the most useful display technique for comparing two quantitative variables….In summarizing the relationship between two quantitative variables, we need to consider:
- Association/Direction (i.e. positive or negative)
- Form (i.e. linear or non-linear)
- Strength (weak, moderate, strong)
How would you describe the relationship between two quantitative variables?
A scatterplot displays the strength, direction, and form of the relationship between two quantitative variables. A correlation coefficient measures the strength of that relationship. The correlation r measures the strength of the linear relationship between two quantitative variables.
Is IQ a quantitative variable?
Variables, whose values are interval-scaled and metrical, are called quantitative data. Typical examples are body weight, income or IQ score. For these variables, we can perform various mathematical calculations, such as the calculation of an arithmetic mean.
Which of the following indicates the strongest relationship between two variables?
Explanation: According to the rule of correlation coefficients, the strongest correlation is considered when the value is closest to +1 (positive correlation) or -1 (negative correlation). A positive correlation coefficient indicates that the value of one variable depends on the other variable directly.
What determines a strong correlation?
The relationship between two variables is generally considered strong when their r value is larger than 0.7. The correlation r measures the strength of the linear relationship between two quantitative variables.
What statistical analysis is done to find how strong a relationship is between two quantitative variables?
Correlation is a bivariate analysis that measures the strength of association between two variables and the direction of the relationship. In terms of the strength of relationship, the value of the correlation coefficient varies between +1 and -1.
Is 0.73 A strong correlation?
The rate of the correlation between variables can be defined in a standardized way. In our example in Figure 1, the correlation between the two tests is 0.73, indicating a strong relationship because it is close to 1. Likewise, a correlation of r = -1 defines a perfect negative relationship between the two variables.
When trying to explain the relationship between two quantitative variables it would be best to use a?
A scatterplot is the most useful display technique for comparing two quantitative variables.
Is there a linear relationship between two quantitative variables?
There is no linear relationship between the two quantitative variables. E. There is no linear relationship between the two quantitative variables. 1.5. He made a mistake in his calculation since the correlation coefficient has to be between minus 1 and 1.
When is the correlation coefficient of bivariate data misleading?
True or false: The correlation coefficient computed on bivariate quantitative data is misleading when the relationship between the two variables is non-linear. or independent variable.
Which is the graphical representation of two quantitative variables?
A graphical representation of two quantitative variables in which the explanatory variable is on the x-axis and the response variable is on the y-axis. When examining a scatterplot, we need to consider the following:
Which is the explanatory variable in a regression?
Unlike in correlation, in regression is does matter which variable is called x and which is called y. In regression, the explanatory variable is always x and the response variable is always y. Both x and y must be quantitative variables.