I am looking for some help on using Chi- squared distribution. Here is the quest

Question

I am looking for some help on using Chi- squared distribution.

Here is the question: Use the chi-squared distribution to test the hypothesis.

An employer polled its employers to see if they agree with the proposed new store hours and whether or not their present shift made a difference in their answers. The customers answered 1 for agree, 2 for don't know, and 3 for disagree. Nine first shift employees answered "agree", 15 second shift employees answered "agree", and 20 third shift employees answered agree. With a 95% confidence level determine whether or not the employees' present shift played a role in their responses to the poll.

Where I am stuck is with setting up the table and knowing which value are the expected and observed.

Where do I find what the expected values were?

What needs to be done to answer the rest of the question?

Thank you!

Number to Agree First Shift 9 Second Shift 15 Third Shift 20

Explanation / Answer

Expected value is average of observed value.

Observed value is which you have got

Chi square Stats=Sum((Observed-Expected)^2/Expected)

degress of freedom=n-1=3-1=2

chi square stats=4.1354

table value=5.991 at 5% los

if chi square test > table value

we reject Ho

but here it is not so, we do not reject Ho at 5% los.

Observed Expected (Observed-Residual) (Observed-Residual)^2 (Observed-Residual)^2/Expected 9 14.67 -5.67 32.1489 2.191472393 15 14.67 0.33 0.1089 0.007423313 20 14.67 5.33 28.4089 1.936530334

Related Questions

Navigate

• Browse (All)
• Browse I
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.