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viva [34]
2 years ago
15

I NEED ASAP DUE IN 20 MINS

Mathematics
1 answer:
11111nata11111 [884]2 years ago
4 0

Answer:

y = 45 / 2x + 50

Step-by-step explanation:

The best equation for the line of the best fit would be y = 45 / 2x + 50.

The slope would be 45 / 2 and the y-intercept would be ( 0 , 50 ).

I used the points, ( 0 , 50 ) and ( 4 , 140 ) to get the equation, slope, and the y-intercept.

I used those points because they were the most accurate ones that I know for now.

Also, remember the formula is, "y = mx + b."

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HK bisects GHJ. Find GHK and KHJ. Angle JHG measures 161
lapo4ka [179]

Answer: m∠GHK=80.5,

m∠KHJ=80.5

Step-by-step explanation:

3 0
3 years ago
Read 2 more answers
Martin collected data from students about whether they played a musical instrument. The table shows his
nydimaria [60]

Answer: 90 students

Step-by-step explanation:

I got this question on my test, and the answer was 90

100% verified! :D

6 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
I've been looking in the study guide but can't find how to solve it
OLga [1]
The answer is -1/16 or -0.0625, do you need to see work?
6 0
3 years ago
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Lol not good with averages pls help
Ivenika [448]
15 is the answer i divided
6 0
3 years ago
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