Each day, a weather forecaster predicts whether or not it will rain. For 80% of rainy days, she correctly predicts that it will rain. For 90% of non-rainy days, she correctly predicts that it will not rain. Suppose that 10% of days are rainy and 90% are non-rainy.
What proportion of the forecasts are correct?

Our required proportion of the forecasts are correct is 89%.

Step-by-step explanation:

Since we have given that

Percentage of rainy days she correctly predicts that it will rain = 80%

Percentage of non rainy days, she correctly predicts that it will not rain = 90%

Percentage of rainy days = 10%

Percentage of non rainy  days = 90%

So, Probability of forecasts are correct is given by

P(rainy day).P(correctly predicted) + P(non rainy day) .P(correctly predicted)

Hence, our required proportion of the forecasts are correct is 89%.

an advantage of the standard deviation is that it increases as the dispersion of the data increases. e. the interquartile range is preferred when the data are not skewed or no have outliers. an advantage of the standard deviation is that it uses all the observations in its computation.

10 down (bang1)

5 up

5down (2)

2.5 up

2.5 down (3)

1.25 up

1.25 down (4)

now add them up : )

hoped i lol