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mel-nik [20]
3 years ago
11

How to ties my shoes? (i am financially bankrupt and can no longer afford velcro nor slip ons)

Mathematics
1 answer:
tankabanditka [31]3 years ago
6 0
Good luck.......................
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Can someone answer this its just boxplots :)))
777dan777 [17]
Nuclear engineer .......
8 0
3 years ago
Nine times a number divided by 2 equals 54.
bazaltina [42]

x = the unknown number

\frac{9x}{2} =54

nine <u>times</u>(multiplication) a number(x) divided(division) by 2 equals(=) 54,

so 9x is divided by 2

4 0
3 years ago
Yen paid $10.50 for 2.5 pounds of pretzels. What price did she pay for each pound of pretzels? Move decimal O $0.42 0 $4.20 Divi
Grace [21]

Answer: The answer is $4.20

Step-by-step explanation:

6 0
2 years ago
An article reports the following data on yield (y), mean temperature over the period between date of coming into hops and date o
skelet666 [1.2K]

Answer:

x1=c(16.7,17.4,18.4,16.8,18.9,17.1,17.3,18.2,21.3,21.2,20.7,18.5)

x2=c(30,42,47,47,43,41,48,44,43,50,56,60)

y=c(210,110,103,103,91,76,73,70,68,53,45,31)

mod=lm(y~x1+x2)

summary(mod)

R output: Call:

lm(formula = y ~ x1 + x2)

Residuals:  

   Min      1Q Median      3Q     Max

-41.730 -12.174   0.791 12.374 40.093

Coefficients:

        Estimate Std. Error t value Pr(>|t|)    

(Intercept) 415.113     82.517   5.031 0.000709 ***  

x1            -6.593      4.859 -1.357 0.207913    

x2            -4.504      1.071 -4.204 0.002292 **  

---  

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1  

Residual standard error: 24.45 on 9 degrees of freedom  

Multiple R-squared: 0.768,     Adjusted R-squared: 0.7164  

F-statistic: 14.9 on 2 and 9 DF, p-value: 0.001395

a).  y=415.113 +(-6.593)x1 +(-4.504)x2

b). s=24.45

c).  y =415.113 +(-6.593)*21.3 +(-4.504)*43 =81.0101

residual =68-81.0101 = -13.0101

d). F=14.9

P=0.0014

There is convincing evidence at least one of the explanatory variables is significant predictor of the response.

e).  newdata=data.frame(x1=21.3, x2=43)

# confidence interval

predict(mod, newdata, interval="confidence")

#prediction interval

predict(mod, newdata, interval="predict")

confidence interval

> predict(mod, newdata, interval="confidence",level=.95)

      fit      lwr      upr

1 81.03364 43.52379 118.5435

95% CI = (43.52, 118.54)

f).  #prediction interval

> predict(mod, newdata, interval="predict",level=.95)

      fit      lwr      upr

1 81.03364 14.19586 147.8714

95% PI=(14.20, 147.87)

g).  No, there is not evidence this factor is significant. It should be dropped from the model.

4 0
3 years ago
Can someone help me with this? I don’t need an explanation I just need the answer thank you :)
Fittoniya [83]

Answer:

87.92 in²

Step-by-step explanation:

pi × (R² - r²) = area

Where R is the radius of the outer circle and r of the inner circle.

Since C = 2pi×r

37.68 = 2×3.14×r

r = 6 in

R = 6 + 2 = 8 in

Therefore,

pi × (R² - r²) = area

Area = 3.14 (8² - 6²)

= 87.92 in²

5 0
3 years ago
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