When you use linear regression to model the data, there will typically be some amount of error between the predicted value as calculated from your model, and each data point. These differences are called "residuals". If those residuals appear to be essentially random noise (i.e. they resemble a normal (a.k.a. "Gaussian") distribution), then that offers support that your linear model is a good one for the data. However, if your errors are not normally distributed, then they are likely correlated in some way which indicates that your model is not adequately taking into consideration some factor in your data. It could mean that your data is non-linear and that linear regression is not the appropriate modeling technique.
yes
With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.
The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.
The mean must be 0 and the variance must be 1.
A bell shaped probability distribution curve is NOT necessarily a normal distribution.
yes
True.
Standardising the observation ensures that the mean is 0 and the standard error is 1. Otherwise the plot could be located anywhere and be concentrated or spread out.
With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.With a single throw of a normal die, the probability is 0.
No. Normal distribution is a continuous probability.
To create a residual plot on a Casio graphing calculator, first enter your data points into a list. Then, use the regression function to calculate the best-fit line for your data. After obtaining the regression equation, compute the residuals by subtracting the predicted values from the actual values and store them in a new list. Finally, plot the residuals against the independent variable using the graphing feature of the calculator.
the probability of gatting a head from a normal coin is
The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.The probability on a single random draw, from a normal deck of cards, is 1/52.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
The probability is zero! There is no such thing as "normal". Every child (and adult) has some unique characteristics and that makes them not normal - in that respect.
A probability density function can be plotted for a single random variable.
To determine if the line of best fit is appropriate for the data, examine the residual plot for randomness. If the residuals are randomly scattered around the horizontal axis without any discernible pattern, it suggests that the linear model is suitable. Conversely, if the residuals display a pattern (such as a curve), it indicates that a linear model may not be the best fit for the data.