A manufacturing company produces part QV2Y for the aerospace industry. This particular part can be manufactured using 3 different production processes. The management wants to know if the quality of the units of part QV2Y is the same for all three processes. The production supervisor obtained the following data: Process 1 had 29 defective units in 240 items, Process 2 produced 12 defective units in 180 items, and Process 3 manufactured 9 defective units in 150 items. At a significance level of 0.05, we performed a chi-square test to determine whether the quality of the items produced appears to be the same for all three processes. What is the null hypothesis

Null hypothesis :

H0 : Quality of parts produced been independent of the production process

We will reject Null hypothesis if value of test statistic ( x^2) > critical value of x^2 at significance level ( ∝ ) 0.05

Step-by-step explanation:

Part produced = QV2Y

Part can be produced using three ( 3 ) different production process

Production process results

process 1 : 29 defective in  240

significance level = 0.05

Null hypothesis :

H0 : Quality of parts produced been independent of the production process

We will reject Null hypothesis if value of test statistic ( x^2) > critical value of x^2 at significance level ( ∝ ) 0.05

critical value = 5.99147   where df = 2

c.35

step-by-step explanation:

8+13=21

21+8=29

29+6=35

x ≥ 18 is your answer

step-by-step explanation:

let "a number" = x

(2/3)x + 17 ≥ 29

isolate the variable (x). do the opposite of pemdas (parenthesis, exponent (& root), multiplication, division, addition, subtraction).

first, subtract 17 from both sides.

(2/3)x + 17 (-17) ≥ 29 (-17)

(2/3)x ≥ 29 - 17

(2/3)x ≥ 12

next, multiply 3/2 to both sides to isolate the x

(3/2)(2/3)x ≥ 12(3/2)

x ≥ 12(3/2)

simplify. multiply, then divide

x ≥ (12 * 3)/2

x ≥ (36)/2

x ≥ 18

x ≥ 18 is your answer

~