Partial product 342 x 405

The Wall Street Journal Corporate Perceptions Study 2011 surveyed readers and asked how each rated the Quality of Management and

kykrilka [37]

Answer:

The calculated χ² = 17.0281 falls in the critical region χ² ≥ 9.49 so we reject the null hypothesis that the quality of management and the reputation of the company are independent and conclude quality of management and the reputation of the company are dependent

The p-value is 0 .001909. The result is significant at p < 0.05

Part b:

40 > 8.5

35> 7.5

25> 4

Step-by-step explanation:

1) Let the null and alternative hypothesis as

H0: the quality of management and the reputation of the company are independent

against the claim

Ha: the quality of management and the reputation of the company are dependent

2) The significance level alpha is set at 0.05

3) The test statistic under H0 is

χ²= ∑ (o - e)²/ e where O is the observed and e is the expected frequency

which has an approximate chi square distribution with ( 3-1) (3-1)= 4 d.f

4) Computations:

Under H0 ,

Observed Expected E χ²= ∑(O-e)²/e

40 35.00 0.71

25 24.50 0.01

5 10.50 2.88

35 40.00 0.62

35 28.0 1.75

10 12.00 0.33

25 25.00 0.00

10 17.50 3.21

15 7.50 7.50

∑ 17.0281

Column Totals 100 70 30 200 (Grand Total)

5) The critical region is χ² ≥ χ² (0.05)2 = 9.49

6) Conclusion:

The calculated χ² = 17.0281 falls in the critical region χ² ≥ 9.49 so we reject the null hypothesis that the quality of management and the reputation of the company are independent and conclude quality of management and the reputation of the company are dependent.

7) The p-value is 0 .001909. The result is significant at p < 0.05

The p- values tells that the variables are dependent.

Part b:

If we take the excellent row total = 70 and compare it with the excellent column total= 100

If we take the good row total = 70 and compare it with the good column total= 80

If we take the fair row total = 50 and compare it with the fair column total= 30

The two attributes are said to be associated if

Thus we see that ( where (A)(B) are row and columns totals and AB are the cell contents)

AB> (A)(B)/N

40 > 1700/200

40 > 8.5

35> 1500/200

35> 7.5

25> 800/200

25> 4

and so on.

Hence they are positively associated

8 0

3 years ago

Jade wants to buy a $200,000 term life insurance policy. She is 34 years old. Using the premium table, what is her annual premiu

AnnZ [28]

Premium rates are usually for premium per fixed face value. Jade's annual premium for a 10 year policy is given by Option b: $1,202

<h3>How to calculate the total annual premium for $x ?</h3>

If its given that the annual premium is $p per $y face value, then we can calculate the annual premium for $1 face value and then use it to calculate annual premium for $x.

Using proportions, we get:

$\rm \$y \: face \: value : \$p \: annual \: premiun\\\\\rm \$1 \: face \: value : \$\dfrac{p}{y} \: annual \: premiun\\\\\rm \$x\:face\: value : \$\dfrac{p \times x}{y} \: annual \: premiun\\$

For given case, from the tables, we see that for age 34, and 10 year life insurance for female gender , there is annual premium of 6.01 per $1000 face value.
Thus, we have p = 6.01, y = 1000

Since Jade wants to buy Life insurance for $200,000, thus, x = $200,000

Putting it in the above derived formula, we get:

$\rm \$x\:face\: value : \$\dfrac{p \times x}{y} \: annual \: premium\\\\\rm \$200000\:face\: value : \$\dfrac{6.01 \times 200000}{1000} \: annual \: premium\\ = \$1202 \: annual \: premiun$