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mihalych1998 [28]
2 years ago
10

Please help me

Mathematics
1 answer:
morpeh [17]2 years ago
6 0

Answer:

No, because the cone has a smaller volume than the ice cream

Step-by-step explanation:

V=4

3πr3=4

3·π·33≈113.09734

Volume of scoop: 113.1 cm^2

V=πr2h

3=π·2.52·10

3≈65.44985

Volume of cone: 65.45 cm^2

65.45 < 113.1

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Help me fill this out thanks
alukav5142 [94]

Answer:

This is an isosceles right triangle, then we have

2 x u^2 = [6sqrt(2)]^2

<=> 2 x u^2 = 72

<=> u^2 = 36

<=> u = 6

Hope this helps!

:)

8 0
3 years ago
Find the length of a rectangle with a perimeter of 148 inches and width of 36 inches.<br> inches
Alexeev081 [22]

Answer:

Perimeter of rectangle = 2L + 2W

2L + 2 * 36 = 148

2L = 148 - 72

2L = 76

L = 38 inches

6 0
2 years ago
Read 2 more answers
How to convert degrees into radians?
Anna11 [10]

1 Degree Radian = π (pie)/ 180 degrees

3 0
2 years ago
An important assumption underlying inferences from a linear regression is that variance in the response variable is reasonably c
rewona [7]

Answer:

A. True

Step-by-step explanation:

Linear regression is "an analysis that assesses whether one or more predictor variables explain the dependent (criterion) variable.  The regression has five key assumptions:

1) Linear relationship : We need to check if the dependnet variable present a linear relationshipThe linearity assumption can best be tested with scatter plots in order to check if we have outliers in the data.

2) Multivariate normality : "The linear regression analysis requires all variables to be multivariate normal".  And we can check this with a histogram or a Q-Q-Plot, usually Normality can be checked with a goodness of fit test like the Kolmogorov-Smirnov test or Shapiro Wilks test.

3) No or little multicollinearity : "Multicollinearity occurs when the independent variables are too highly correlated with each other". And we can check this with a correlation matrix, variance inflation factor (VIF's), correlation index and other statistics.

4) No auto-correlation : The "Autocorrelation happens when the residuals are not independent from each other in the data". And usually we can test this with the Durbin-Watson test.

5) Homoscedasticity: MEans that we need constant variance for the linear model. The scatter plot is good way to check whether the data are homoscedastic. And we can interpret this condition as "that variance in the response variable is reasonably consistent across the range of an explanatory factor (otherwise known as homoscedasticity)"

So then the statement is TRUE.

5 0
3 years ago
Help pls ill give extra points
Sergeu [11.5K]
I believe it is positive so option 2
7 0
2 years ago
Read 2 more answers
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