All categories

3 years ago

Write 0.000739 in scientific notation.

Mathematics

2 answers:

jek_recluse [69]3 years ago

6 0

Answer:

7.39 × 10-4^-4

Step-by-step explanation:

fenix001 [56]3 years ago

5 0

Answer:

7.39 × 10-⁴

Step-by-step explanation:

m × 10ⁿ, where m is a number between 1 and 10 ( 1 ≤ |m| < 10 ) and the exponent n is a positive or negative integer.

You might be interested in

Which is faster 15 feet per second or 12 miles per hour

Ierofanga [76]

12 miles per hour, it’ll be 17.6 feet per second.

6 0

3 years ago

Read 2 more answers

A map using a scale inch of 1 to 5 miles shows a section of land with an area of 3.2 in.² what is the actual area of the section

Karolina [17]

Answer:

The actual area of land is 80 mi² .

Step-by-step explanation:

Given that we have to find the actual area so first we have to square the ratio(scale factor) :

1 in : 5 mi

(1 in)² : (5 mi)²

1 in² : 25 mi²

Next, the actual area will be :

1 in² = 25 mi²

(1 × 3.2) in² = (25 × 3.2) mi²

3.2 in² = 80 mi²

6 0

3 years ago

the vertices of triangle PQR are P(-3, 8), Q(-6, -4), and R(1, 1). If you reflect triangle PQR across the x-axis, what will be t

otez555 [7]

Answer:

The coordinates of the vertices of the image will be:

P'=(-3,-8)

Q'=(-6,4)

R'=(1,-1)

Step-by-step explanation:

If you reflect a point P=(x,y) across the x-axis, the coordinates of the image will be P'=(x,-y), then:

P=(-3,8)=(xp,yp)→xp=-3, yp=8→P'=(xp,-yp)→P'=(-3,-8)

Q=(-6,-4)=(xq,yq)→xq=-6, yq=-4→Q'=(xq,-yq)=(-6,-(-4))→Q'=(-6,4)

R=(1,1)=(xr,yr)→xr=1, yr=1→R'=(xr,-yr)→R'=(1,-1)

3 0

3 years ago

Given f(x) = x2 + 4x − 1 and g(x) = 5x − 7, identify (fg)(x).

8_murik_8 [283]

<span> f(x) = x^2 + 4x − 1 and g(x) = 5x − 7
</span>(fg)(x) = (x^2 + 4x − 1)(5x − 7)
(fg)(x) = 5x^3 + 20x^2 - 5x - 7x^2 - 28x + 7
(fg)(x) = 5x^3 + 13x^2 - 33x + 7

answer is C. third choice

(fg)(x) = 5x^3 + 13x^2 - 33x + 7

4 0

3 years ago

g Minimizing the sum of the squared deviations around the line is called: predictor regression. mean squared error technique. le

Alex787 [66]

Minimizing the sum of the squared deviations around the line is called Least square estimation.

It is given that the sum of squares is around the line.

Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.

To learn more about regression visit: brainly.com/question/14563186

#SPJ4

3 0

1 year ago