Casio ALGEBRA FX 2.0 Manuale utente

Examples

examples

k1-Sample ZTest

Set Up

1. On the icon menu, select STAT2.

Execution

2. When using list data (List is selected as the Data parameter), be sure to input data into

the list first.

3. 3(TEST)b(Z)b(1-Smpl) ... 1-Sample ZTest

4. Set calculation parameters.

5. Align the cursor with [Execute]

1(CALC) ... Performs calculation.

6(DRAW) ... Draws graph.

examples

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Example Five new members of a football team are timed for the 100-

meter dash, yielding the following times.

A: 12.5 B: 11.6 C: 10.8 D: 12.8 E: 11.4

The average time of current team members is 11.4 seconds,

with a standard deviation of 1.30. Test the null hypothesis that

the times of the five new members are at the same level as

current team members at the 0.05 level of significance.

Procedure

1mSTAT2

2 bc.fwbb.gwba.iw

bc.iwbb.ew

33(TEST) b(Z)b(1-Smpl)

41(LIST) c

1(≠) c

bb.ew

b.dw

1(LIST) bwc

1(1)c

1(None)c

51(CALC)

6(DRAW)

Result Screen

Since P = 0.47003508 > 0.05 (level of significance), we can't reject the null hypothesis and

can conclude the times of the five new numbers is at the same level as current team

members.

examples

k2-Sample ZTest

Set Up

1. On the icon menu, select STAT2.

Execution

2. When using list data (List is selected as the Data parameter) , be sure to input data into

the list first.

3. 3(TEST)b(Z)c(2-Smpl) ... 2-Sample ZTest

4. Set calculation parameters.

5. Align the cursor with [Execute]

1(CALC) ... Performs calculation.

6(DRAW) ... Draws graph.

examples

○○○○○

Example A consumer group is testing camp stoves. To test the heating capacity

of a stove they measure the time required to bring 2 qt of water from

50qq

qF to boiling (at sea level). Two competing models are under

consideration. 36 stoves of each model were tested and the following

results were obtained.

Model 1: mean time oo

o1= 11.5min; standard deviation σ1= 2.4min

Model 2: mean time oo

o2= 10 min; standard deviation σ2= 3 min

Is there any difference between the performances of these two

models? (Use a 5% level of significance.)

Procedure

1mSTAT2

23(TEST) b(Z)c(2-Smpl)

32(VAR) c

1(≠) c

c.ew

bb.fw

dgw

baw

dgw

1(None) c

41(CALC)

6(DRAW)

Result Screen

Since P = 0.01914957 < 0.05 (level of significance), we reject the null hypothesis µ1-µ2 =0

and conclude the performances of the two models are different.

examples

k1-Prop ZTest

Set Up

1. On the icon menu, select STAT2.

Execution

2. 3(TEST)b(Z)d(1-Prop) ... 1-Prop ZTest

3. Set calculation parameters.

4. Align the cursor with [Execute]

1(CALC) ... Performs calculation.

6(DRAW) ... Draws graph.

examples

○○○○○

Example A team of eye surgeons has developed a new technique for a risky eye

operation to restore the sight of people blinded from a certain disease.

Under the old method it is known that only 30% of the patients who

undergo this operation recover their eyesight. Suppose that surgeons

in various hospitals have performed a total of 250 operations using

the new method and that 93 have been successful (the patients fully

recovered their sight). Can we justify the claim that the new method is

better than the old one?(Use a 1% level of significance.)

Procedure

1mSTAT2

23(TEST) b(Z)d(1-Prop)

33(>) c

.dw

jdw

cfaw

1(None) c

41(CALC)

6(DRAW)

Result Screen

Since P = 6.4915e-3 < 0.01 (level of significance), we can reject the null hypothesis that the

successful probability of new operation is 0.3 and conclude that it can be said the new

method obtains good results more than existing method. That is to say it is more effective by

new methods.

k2-Prop ZTest

Set Up

1. On the icon menu, select STAT2.

Execution

2. 3(TEST)b(Z)e(2-Prop) ... 2-Prop ZTest

3. Set calculation parameters.

4. Align the cursor with [Execute]

1(CALC) ... Performs calculation.

6(DRAW) ... Draws graph.

examples

○○○○○

Example The County Clerk wishes to improve voter registration. One method

under consideration is to send reminders in the mail to all citizens in

the county who are eligible to register. As a pilot study to determine if

this method will actually improve voter registration, a random sample

of 1224 potential voters was taken. Then this sample was randomly

divided into two groups.

Group A : There were 612 people in this group. No reminders to

voters from this group who registered was 280.

Group B : This group also contained 612 people. Reminders were

sent in the mail to each member in the group, and the

number who registered to vote was 335.

The County Clerk claims that the proportion of people to register was

significantly greater in group B. On the basis of this claim the clerk

recommends that the project be funded for the entire population of

Macek County. Use 5% level of significance to test the claim that the

proportion of potential voters who registered was greater in group B,

the group that received reminders.

Procedure

1mSTAT2

23(TEST) b(Z)e(2-Prop)

32(<) c

ciaw

gbcw

ddfw

gbcw

1(None) c

41(CALC)

6(DRAW)

Result Screen

Since P = 8.3277e-4 < 0.05 (level of significance), we can reject the null hypothesis (P1>P2)

and conclude that the County Clerk‘s claim is valid at the 0.05 level of significance.

k1-Sample tTest

Set Up

1. On the icon menu, select STAT2.

Execution

2. When using list data (List is selected as the Data parameter), be sure to input data into

the list first.

3. 3(TEST)c(T)b(1-Smpl) ... 1-Sample tTest

4. Set calculation parameters.

5. Align the cursor with [Execute]

1(CALC) ... Performs calculation.

6(DRAW) ... Draws graph.

examples

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