Answer:
Smallest number = 3500
Step-by-step explanation:
Rounding of numbers involve replacing numbers with simpler numbers. In order to round a number to the nearest thousand, the last 3 digits of the number should be considered. If the last 3 digits are less than 500, the number is rounded down(the thousand figure is unaffected), but if the last 3 digits are greater or equal to 500, the number is rounded up.
In this case, Yuri is thinking of a 4-digit whole number and he rounds his number to the nearest thousand. Since his answer is 4000, the smallest number yuri could be thinking of would be 3500 and the highest number he could be thinking of is 4499.
Thus, the smallest number Yuri could be thinking of is 3500
Answer:
Store A offers the least amount for the sofa
Step-by-step explanation:
Cost of sofa =$500
For store A
Discount =20% off
The amount of the discount is
=20/100*500
=0.2*500
=$100
6.5% sales tax
The amount of tax is
=6.5/100*500
=0.065*500
=$32.5
Total cost of the sofa
=500-100+32.5
=400+32.5
=$432.5
For store B
Discount =30% off
The amount of the discount is
=30/100*500
=0.3*500
=$150
Shipping fee $85
Total cost of sofa
=500-150+85
=350+85
=$435
Step-by-step explanation:
Start by writing 492,623 in standard form
4 hundred thousands + 9 ten thousands + 2 thousands + 6 hundreds + 2 tens + 3 ones
We can write this in other ways by moving a digit to the next smaller place value. For example, we move the 4 one place to the right to get 49 ten thousands:
49 ten thousands + 2 thousands + 6 hundreds + 2 tens + 3 ones
Then, we can move the 49 ten thousands to the right to get 492 thousands, and we can move 6 hundreds to the right to get 62 tens.
492 thousands + 62 tens + 3 ones
Or, we can do this:
4926 hundreds + 23 ones
Answer:
The homoskedasticity-only F-statistic and the heteroskedasticity-robust F-statistic typically are different.
Step-by-step explanation:
An F statistic is a value derived by running an ANOVA test or a regression analysis to find out if the means between two populations are significantly different.
The homoskedasticity-only” F-statistic is derived by running two regressions, one under the null hypothesis and one under the alternative hypothesis. If the “unrestricted” model fits sufficiently better, reject the null.
In the first regression, the restricted regression (the null hypothesis) is forced to be true. This is the regression in which all the coefficients are set to zero; the relevant regressors are excluded from the regression. In the second regression, the unrestricted regression, the alternative hypothesis is allowed to be true. If the sum of squared residuals is sufficiently smaller in the unrestricted than the restricted regression, then the test rejects the null hypothesis
The heteroskedasticity-robust F-statistic is built in to STATA (“test” command); this tests all q restrictions at once.
The homoskedasticity-only F-statistic is important historically (and also in practice), and can help intuition, but isn’t valid when there is heteroskedasticity
