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emmainna [20.7K]
1 year ago
5

. En un concesionario de coches hay modelos de varios colores. Los rojos suponen 1 6 del total, los azules, 2 9 del total, y los

blancos, 4 15 del total.
Mathematics
1 answer:
Sholpan [36]1 year ago
4 0

Complete question :

En un concesionario de coches hay modelos de varios colores. Los rojos suponen 1/6 del total, los azules, 2/9 del total, y los blancos, 4/15 del total.

a)¿Cuál de esos colores es el más frecuente?

b) Si hay 40 coches azules, ¿cuántos hay en total?

Responder:

Coches blancos

180 coches

Explicación paso a paso:

Dado que:

Rojo = 1/6 del total

Azul = 2/9 del total

Blanco = 4/15 del total

Para determinar qué color es el más alto, convierta los valores en decimal:

1/6 = 0,166667

2/9 = 0,2222

15/4 = 0,26667

Por lo tanto;

4/15> 2/9> 1/6

Por tanto, los coches blancos son los que más

2.)

Sea Número total = x

Por lo tanto,

2/9 de x = 40

2x / 9 = 40

2x = 360

x = 180

Por tanto, hay 180 coches en total.

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Answer:

p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91

So on this case for the significance level assumed \alpha=0.05 we see that p_v >\alpha so then we can conclude that the result is NOT significant. And we don't have enough evidence to reject the null hypothesis.

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

Step-by-step explanation:

Let's suppose that we have the following linear model:

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Where Y is the dependent variable and X the independent variable. \beta_0 represent the intercept and \beta_1 the slope.  

In order to estimate the coefficients \beta_0 ,\beta_1 we can use least squares procedure.  

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_1 = 0

Alternative hypothesis: \beta_1 \neq 0

Or in other words we want to check is our slope is significant (X have an effect in the Y variable )

In order to conduct this test we are assuming the following conditions:

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The significance level assumed on this case is \alpha=0.05

The standard error for the slope is given by this formula:

SE_{\beta_1}=\frac{\sqrt{\frac{\sum (y_i -\hat y_i)^2}{n-2}}}{\sqrt{\sum (X_i -\bar X)^2}}

Th degrees of freedom for a linear regression is given by df=n-2 since we need to estimate the value for the slope and the intercept.  

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_1}{SE_{\beta_1}}

The p value on this case would be given by:

p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91

So on this case for the significance level assumed \alpha=0.05 we see that p_v >\alpha so then we can conclude that the result is NOT significant. And we don't have enough evidence to reject the null hypothesis.

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

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5 equally sized boxes of cake mix fell off the back of Jake's truck. Together they weigh 925.98 pounds. How much does each ball
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we are given

5 equally sized boxes of cake mix fell off the back of Jake's truck

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Together they weigh 925.98 pounds

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Answer:

The third and fourth options.

Step-by-step explanation:

You simplify the inequality first...

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The second option is basically -5x < 15; x > -3; that's incorrect.

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Mode is a statistical term that refers to the most frequently occurring number found in a set of numbers.

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Since there are 10 terms.

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Median = 5th observation.

Since, the 5th observation is 55.6.

Therefore, the median is 55.6

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2 years ago
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