0
What else can I help you with?
What are the three ways to describe data in a scatter plot?
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
What would a strong association but weak correlation look like?
If the form is nonlinear (like if the data is in the shape of a parabola) then there could be a strong association and weak correlation.
What does a scatter plot look like Having a positive linear correlation?
It looks like a straight line increasing as the x-values increase. So basically a line that goes from the bottom left area to the top right area on a graph.
In a correlation coefficient the difference between r and r squared?
r is correlation and can be positive or negative. If you want an analogy, consider it like the slope of a line. If the slope is negative, the line slopes downward and therelationship between the two variables (x & y) are inverse. That is, as x increases, y will decrease. If r is positive, then the line slopes upward and as x increases so does y. Now if x equals or is close to zero, there is no significant relationship between the two variables ... as x increases y does not change or fluctuates between positive and negative changes. The closer r is to +1 or -1, the stronger the relationship between x and y.
What is the difference between a scatter plot and a line graph?
Scatter plots and Line graphs have similarities in that they both use an X-Y axis. But a line graph has a line or curve to describe a formula like Y=2X+5, a Scatter plot is a collection of X-Y coordinates that have no real formula due to real life uncertainties (Heisenberg), but, once plotted, can provide a clue to a single formula.
How do you find out what correlation a scatter plot has?
It is easy to find the correlation. First you see how far apart the dots are. if they are going UP like this / <---- it means its a positive correlation. if its like this \ <---- its a negative correlation. if its everywhere its a neutral (although they almost never do them in tests). To find out the strength is your opinion. If alot are grouped together almost making a line its a Strong correlation. Then you decide if its a Strong or Weak correlation depending on how close together the dots are. So put them together in a 1 mark question like::::it is a Strong Positive Correlation
What are the three ways to describe data in a scatter plot?
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
How do you read a scatter graph?
Scatter-plot shows correlation between two different variables (one on the y-axis, the other on x-axis). If there is linear correlation, the scatter-points form a straight line from zero (origo) to some direction. The more cloud-like distribution the scatter-plot does have, the less those variables in question have correlation or dependence with each other.
What are the disadvantages of a scatter graph?
A scatter graph may use a positive correlation or negative correlation, to shows points of the graph in either a dipping or climbing line, and is fairly easy to read the data. A zero correlation is when the points are scattered across the graph and this can make seeing the data difficult. It's a bit like "dot to dot" in a children's puzzle book, but without the numbers at the side of the dots!
What would a strong association but weak correlation look like?
If the form is nonlinear (like if the data is in the shape of a parabola) then there could be a strong association and weak correlation.
What does a scatter plot look like Having a positive linear correlation?
It looks like a straight line increasing as the x-values increase. So basically a line that goes from the bottom left area to the top right area on a graph.
What is a way to look at how one set of data is related to another is called?
A way to look at how one set of data is related to another is called correlation analysis. This statistical method assesses the strength and direction of the relationship between two variables, indicating whether they move together (positive correlation), move in opposite directions (negative correlation), or have no discernible relationship. Tools such as scatter plots and correlation coefficients, like Pearson's r, are commonly used to visualize and quantify these relationships.
Examples of negative correlation?
Well, say the temperature out side is get getting higher. As the temperature gets higher people will start to wear less clothing. So, as the temperature increases the amount of clothing people wear will decrease. Which on a scatter plot graph would look like a slant moving "down" and to the right, which you would call a negative correlation. It's the opposite for a positive correlation, the colder it gets the more clothing people will wear...
Is r equal .12 a strong correlation in social sciences?
A correlation of .12 is considered weak in social sciences. It suggests that there is a very minor relationship between the variables being studied. Strong correlations are typically closer to 1 or -1.
What are the possible ranges of correlation coefficients?
The possible range of correlation coefficients depends on the type of correlation being measured. Here are the types for the most common correlation coefficients: Pearson Correlation Coefficient (r) Spearman's Rank Correlation Coefficient (ρ) Kendall's Rank Correlation Coefficient (τ) All of these correlation coefficients ranges from -1 to +1. In all the three cases, -1 represents negative correlation, 0 represents no correlation, and +1 represents positive correlation. It's important to note that correlation coefficients only measure the strength and direction of a linear relationship between variables. They do not capture non-linear relationships or establish causation. For better understanding of correlation analysis, you can get professional help from online platforms like SPSS-Tutor, Silverlake Consult, etc.
Which charge has strong force of attraction?
Neither charge on its own has an attractive force. Opposite charges (positive-negative) will attract while like charges (negative-negative or positive-positive) will repel.
How will you interpret the coefficient of correlation?
Correlation is a measure of the strength of a linear relationship between two variables. In theory it ranges between -1 and +1, although in practice, random and observation error make this value smaller.Near -1, the correlation is very strongly negative, which means that an increase in one variable is accompanied by a decrease in the other.Near +1, the correlation is very strongly positive, which means that an increase in one variable is accompanied by an increase in the other.Near 0, the correlation is weak and there is no linear pattern in which the two variables change.There are two very critical points to remember:Correlation does not measure causation. For example, the number of cars on the road is correlated to my age but my getting older does not cause more cars to be made and cars do not cause me to grow old (at least, not with most drivers!)Correlation will only measure a linear relationship. If you examine a relationship like y = x2, over a symmetric interval, the correlation coefficient will be close to 0. But there is, clearly, a very strong relationship - just that it is not linear.Finally, the importance of any correlation coefficient is subjective and depends on the context. A correlation coefficient that is high for a sociological study may be considered moderate for a high school physics experiment.
