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vladimir2022 [97]
3 years ago
9

O preço do diesel sofreu três alterações ao longo do último trimestre de 2017. A primeira alteração foi em outubro, cujo aumento

foi de 10% no preço inicial do produto. Em novembro, houve um novo aumento, agora de 20%. Em dezembro, em função das datas festivas, 12% de aumento sobre o preço final de novembro. A variação do preço da diesel acumulada no último trimestre do ano em relação ao seu preço inicial foi de:
Mathematics
1 answer:
EleoNora [17]3 years ago
5 0

Answer:

47.84%

Step-by-step explanation:

The easiest method to solve this exercise is to assume that the starting diesel price is 100 reais.

Now we will calculate each increase with our assumption:

1. Initial price plus 10% increase, therefore:

100 + 100 * 0.1 = 110 reais

2. Additional 20% increase in relation to 110 reais:

110 + 110 * 0.2 = 132 reais

3. Additional 12% increase in relation to 132 reais:

132 + 132 * 0.12 = 147.84 reais.

What it means is that the price would be 147.84 reais.

Since our assumption is 100, we can know that there was an increase of almost 47.84% in relation to the initial price that we assumed at the beginning.

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Three teachers share 2 packs of paper equally.
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Simplify x^2-4x+4/x^2-4
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Answer:

x2 - 4x - 4

 ———————————

    x - 2  

Step-by-step explanation:

4 0
3 years ago
anthony bought an 8 foot board.He cut off 3/4 of the board to build a shelf,and gave 1/3 of the rest to his brother for an art p
e-lub [12.9K]
Convert your feet to inches.
So 8 times by 12 = 96 inches
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7 0
3 years ago
Read 2 more answers
A research firm tests the miles-per-gallon characteristics of three brands of gasoline. Because of different gasoline performanc
Anni [7]

Answer:

A.) At α = 0.05, is there a significant difference in the mean miles-per-gallon characteristics of the three brands of gasoline.

B.)<u><em>The advantage of attempting to remove the block effect is</em></u>

The completely randomized designs does not prove that H0 is incorrect only that it cannot be rejected.

Step-by-step explanation:

<em><u /></em>

<em><u>Using Two-way ANOVA method</u></em>

Given problem

<em><u>Observation              I          II       III          Row total (xr)</u></em>

A                              18 21 20            59

B                            24 26 27             77

C                            30 29 34             93

D                            22 25 24            71

<u>E                            20 23 24           63                      </u>

Col total (xc)             114 124 129        367

∑x²=9233→(A)

∑x²c/r

=1/5(114²+124²+129²)

=1/5(12996+15376+16641)

=1/5(45013)

=9002.6→(B)

∑x²r/c

=1/3(59²+77²+93²+71²+67²)

=1/3(3481+5929+8649+5041+4489)

=1/3(27589)

=9196.3333→(C)

(∑x)²/n

=(367)²/15

=134689/15

=8979.2667→(D)

Sum of squares total

SST=∑x²-(∑x)²/n

=(A)-(D)

=9233-8979.2667

=253.7333

Sum of squares between rows

SSR=∑x²r/c-(∑x)²/n

=(C)-(D)

=9196.3333-8979.2667

=217.0667

Sum of squares between columns

SSC=∑x²c/r-(∑x)²/n

=(B)-(D)

=9002.6-8979.2667

=23.3333

Sum of squares Error (residual)

SSE=SST-SSR-SSC

=253.7333-217.0667-23.3333

=13.3333

<u>ANOVA table</u>

Source                 Sums         Degrees      Mean Squares

of Variation       of Squares   of freedom

<u>                               SS                 DF              MS       F p-value</u>

B/ w     SSR=217.0667              4 MSR=54.2667    32.56 0.0001

rows

B/w     SSC=23.3333         c-1=2 MSC=11.6667        7 0.01

columns

<u>Error (residual)SSE=13.3333 (r-1)(c-1)=8 MSE=1.6667                  </u>

<u>Total SST=253.7333 rc-1=14                                                        </u>

Conclusion:

<u> 1. F for between Rows</u>

The critical region for F(4,8) at 0.05 level of significance=3.8379

The calculated F for Rows=32.56>3.8379

Therefore H0 is rejected

<u>2. F for between Columns</u>

The critical region for F(2,8) at 0.05 level of significance=4.459

We see that the calculated F for Colums=7>4.459

therefore H0 is rejected,and concluded that there is significant differentiating between columns

<u><em>Part B:</em></u>

To analyze the data for completely  randomized designs click on anova two factor without replication  in the data analysis dialog box of the excel spreadsheet.

The following table is obtained

Source DF             Sum                  Mean           F Statistic

<u>                 (df1,df2)    of Square (SS) Square (MS)                    P-value</u>

Factor A       1 1496.5444 1496.5444 769.6514          0.001297

Rows

Factor B -     2 19.4444           9.7222               5                  0.1667

Columns

Interaction

AB               2    3.8889   1.9444        0.1013         0.9045

<u> Error     12   230.4            19.2                                           </u>

<u>Total 17 1750.2778 102.9575                                                         </u>

<u />

<u>Factor - A- Rows</u>

Since p-value < α, H0 is rejected.

<u>Factor - B- Columns</u>

Since p-value > α, H0 can not be rejected.

The averages of all groups assume to be equal.

<u>Interaction AB</u>

Since p-value > α, H0 can not be rejected.

<u><em>The advantage of attempting to remove the block effect is</em></u>

The completely randomized designs does not prove that H0 is incorrect only that it cannot be rejected.

3 0
3 years ago
Eu preciso de ajuda pfvr:(
belka [17]
I’m not a true percent sure but I think it’s C
8 0
3 years ago
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