The residual plot for a data set is shown.

Mathematics

2 answers:

Stolb23 [73]3 years ago

7 0

Here are the CORRECT answers.

Please leave a thanks.

Darya [45]3 years ago

6 0

Answer:

The regression line is not a good model because the residuals are not randomly distributed.

Step-by-step explanation:

In a regression, the residual is the difference between the observed values and the predicted values.

If the points in a residual plot are randomly dispersed, a linear regression model is appropriate for the data.

In this case, a pattern is present (the plot is similar to a sine plot); this suggest that a non-linear regression would be better.

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Suppose that birth weights are normally distributed with a mean of 3466 grams and a standard deviation of 546 grams. Babies weig

Anon25 [30]

Answer:

3.84% probability that it has a low birth weight

Step-by-step explanation:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this problem, we have that:

$\mu = 3466, \sigma = 546$