Answer:
Yes you are right on both.
Step-by-step explanation:
Plz make brainliest
Answer:
Step-by-step explanation:
The sum of angle measures is ...
(7x +13)° +(83 -2x)° = 141°
5x +96 = 141 . . . . . collect terms, divide by °
5x = 45 . . . . . . . . . subtract 96
x = 9 . . . . . . . . . . . divide by 5
7x +13 = 7·9 +13 = 76 . . . . . find m∠J
m∠J = 76°
m∠K = 141° -76°
m∠K = 65°
Answer:
x = -1
Step-by-step explanation:
-18=15-3(6x+5) Distributive Property
-18=15-18x-15 Combining like terms.
-18=18x Divide by the coefficient.
-1=x
The first step is to find the area of the figure amd then multiply it by the weight of per metre...
<h3>Step 1</h3>

- Length = 60 cm = 0.6 metre
- Width = 200 cm = 2 metre


<h3>Now,</h3>
- Weight of 1 metre² = 0.9 kg
<h3>So, The weight of 1.2 m² is; </h3>

The framework is made up of 5 rods, So the weight will be
➪ <em>T</em><em>h</em><em>u</em><em>s</em><em>,</em><em> </em><em>T</em><em>h</em><em>e</em><em> </em><em>w</em><em>e</em><em>i</em><em>g</em><em>h</em><em>t</em><em> </em><em>o</em><em>f</em><em> </em><em>t</em><em>h</em><em>e</em><em>f</em><em>r</em><em>a</em><em>m</em><em>e</em><em>w</em><em>o</em><em>r</em><em>k</em><em> </em><em>i</em><em>s</em><em> </em><em>6</em><em> </em><em>k</em><em>i</em><em>l</em><em>o</em><em>g</em><em>r</em><em>a</em><em>m</em><em>s</em><em>.</em><em>.</em><em>.</em><em>~</em>
Answer:
a) 
b) 
Step-by-step explanation:
The proportion of defective gadgets for this factory is p=0.2.
If a sample of n=100 gadgets is taken from the production, we can model the amount of defectives gadgets in this sample as a binomial random variable.
The probability of having k defectives in the sample can be written as:

Then, we can write the expression to calculate the probabilities of A: "less than 15 gadgets are mildly defective":

If we approximate this binomial distribtution to a normal distribution, we can calculate the new parameters as:

The continuity factor is applied for the change from a discrete distribution (binomial) to a continous distribution (normal). Then we have:

Now, we can calculate the probability P(A):
