# apple orchard example
prop.test(35,200,p=.2,correct=0)
prop.test(26,200,p=.2,correct=0)
prop.test(45,200,p=.2,correct=0)
prop.test(54,200,p=.2,correct=0)
prop.test(52,200,p=.2,correct=0)
#  tax law change example
prop.test(52,100,p=.5,correct=0)
prop.test(64,100,p=.5,correct=0)
prop.test(64,90,p=.5,correct=0)
# shipment of electronic devices example
prop.test(16,200,p=.06,correct=0)
prop.test(20,200,p=.06,correct=0)
# machine parts example
prop.test(54,200,p=.35,correct=0)
# Mendel's flower color experiment
prop.test(705,929,p=.75,correct=0)
# all of the above with continuity correction
# apple orchard example
prop.test(35,200,p=.2,correct=1)
prop.test(26,200,p=.2,correct=1)
prop.test(45,200,p=.2,correct=1)
prop.test(54,200,p=.2,correct=1)
prop.test(52,200,p=.2,correct=1)
#  tax law change example
prop.test(52,100,p=.5,correct=1)
prop.test(64,100,p=.5,correct=1)
prop.test(64,90,p=.5,correct=1)
# shipment of electronic devices example
prop.test(16,200,p=.06,correct=1)
prop.test(20,200,p=.06,correct=1)
# machine parts example
prop.test(54,200,p=.35,correct=1)
# Mendel's flower color experiment
prop.test(705,929,p=.75,correct=1)

-------------- results --------------------

> # apple orchard example
> prop.test(35,200,p=.2,correct=0)

	1-sample proportions test without continuity
	correction

data:  35 out of 200, null probability 0.2
X-squared = 0.7812, df = 1, p-value = 0.3768
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.1286052 0.2336443
sample estimates:
    p
0.175

> prop.test(26,200,p=.2,correct=0)

	1-sample proportions test without continuity
	correction

data:  26 out of 200, null probability 0.2
X-squared = 6.125, df = 1, p-value = 0.01333
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.09028202 0.18366352
sample estimates:
   p
0.13

> prop.test(45,200,p=.2,correct=0)

	1-sample proportions test without continuity
	correction

data:  45 out of 200, null probability 0.2
X-squared = 0.7812, df = 1, p-value = 0.3768
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.1726237 0.2877412
sample estimates:
    p
0.225

> prop.test(54,200,p=.2,correct=0)

	1-sample proportions test without continuity
	correction

data:  54 out of 200, null probability 0.2
X-squared = 6.125, df = 1, p-value = 0.01333
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.2132345 0.3354344
sample estimates:
   p
0.27

> prop.test(52,200,p=.2,correct=0)

	1-sample proportions test without continuity
	correction

data:  52 out of 200, null probability 0.2
X-squared = 4.5, df = 1, p-value = 0.03389
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.2041383 0.3249075
sample estimates:
   p
0.26

> #  tax law change example
> prop.test(52,100,p=.5,correct=0)

	1-sample proportions test without continuity
	correction

data:  52 out of 100, null probability 0.5
X-squared = 0.16, df = 1, p-value = 0.6892
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.4231658 0.6153545
sample estimates:
   p
0.52

> prop.test(64,100,p=.5,correct=0)

	1-sample proportions test without continuity
	correction

data:  64 out of 100, null probability 0.5
X-squared = 7.84, df = 1, p-value = 0.00511
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.5423540 0.7272878
sample estimates:
   p
0.64

> prop.test(64,90,p=.5,correct=0)

	1-sample proportions test without continuity
	correction

data:  64 out of 90, null probability 0.5
X-squared = 16.0444, df = 1, p-value = 6.187e-05
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.6103596 0.7945787
sample estimates:
        p
0.7111111

> # shipment of electronic devices example
> prop.test(16,200,p=.06,correct=0)

	1-sample proportions test without continuity
	correction

data:  16 out of 200, null probability 0.06
X-squared = 1.4184, df = 1, p-value = 0.2337
alternative hypothesis: true p is not equal to 0.06
95 percent confidence interval:
 0.04984059 0.12598949
sample estimates:
   p
0.08

> prop.test(20,200,p=.06,correct=0)

	1-sample proportions test without continuity
	correction

data:  20 out of 200, null probability 0.06
X-squared = 5.6738, df = 1, p-value = 0.01722
alternative hypothesis: true p is not equal to 0.06
95 percent confidence interval:
 0.06567045 0.14940581
sample estimates:
  p
0.1

> # machine parts example
> prop.test(54,200,p=.35,correct=0)

	1-sample proportions test without continuity
	correction

data:  54 out of 200, null probability 0.35
X-squared = 5.6264, df = 1, p-value = 0.01769
alternative hypothesis: true p is not equal to 0.35
95 percent confidence interval:
 0.2132345 0.3354344
sample estimates:
   p
0.27

> # Mendel's flower color experiment
> prop.test(705,929,p=.75,correct=0)

	1-sample proportions test without continuity
	correction

data:  705 out of 929, null probability 0.75
X-squared = 0.3907, df = 1, p-value = 0.5319
alternative hypothesis: true p is not equal to 0.75
95 percent confidence interval:
 0.7303435 0.7852854
sample estimates:
        p
0.7588805

> # all of the above with continuity correction
> # apple orchard example
> prop.test(35,200,p=.2,correct=1)

	1-sample proportions test with continuity correction

data:  35 out of 200, null probability 0.2
X-squared = 0.6328, df = 1, p-value = 0.4263
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.1264402 0.2363814
sample estimates:
    p
0.175

> prop.test(26,200,p=.2,correct=1)

	1-sample proportions test with continuity correction

data:  26 out of 200, null probability 0.2
X-squared = 5.6953, df = 1, p-value = 0.01701
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.08819814 0.18648006
sample estimates:
   p
0.13

> prop.test(45,200,p=.2,correct=1)

	1-sample proportions test with continuity correction

data:  45 out of 200, null probability 0.2
X-squared = 0.6328, df = 1, p-value = 0.4263
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.1703931 0.2904135
sample estimates:
    p
0.225

> prop.test(54,200,p=.2,correct=1)

	1-sample proportions test with continuity correction

data:  54 out of 200, null probability 0.2
X-squared = 5.6953, df = 1, p-value = 0.01701
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.2109568 0.3380601
sample estimates:
   p
0.27

> prop.test(52,200,p=.2,correct=1)

	1-sample proportions test with continuity correction

data:  52 out of 200, null probability 0.2
X-squared = 4.1328, df = 1, p-value = 0.04206
alternative hypothesis: true p is not equal to 0.2
95 percent confidence interval:
 0.2018704 0.3275428
sample estimates:
   p
0.26

> #  tax law change example
> prop.test(52,100,p=.5,correct=1)

	1-sample proportions test with continuity correction

data:  52 out of 100, null probability 0.5
X-squared = 0.09, df = 1, p-value = 0.7642
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.4183183 0.6201278
sample estimates:
   p
0.52

> prop.test(64,100,p=.5,correct=1)

	1-sample proportions test with continuity correction

data:  64 out of 100, null probability 0.5
X-squared = 7.29, df = 1, p-value = 0.006934
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.5372745 0.7318279
sample estimates:
   p
0.64

> prop.test(64,90,p=.5,correct=1)

	1-sample proportions test with continuity correction

data:  64 out of 90, null probability 0.5
X-squared = 15.2111, df = 1, p-value = 9.614e-05
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
 0.6045394 0.7993990
sample estimates:
        p
0.7111111

> # shipment of electronic devices example
> prop.test(16,200,p=.06,correct=1)

	1-sample proportions test with continuity correction

data:  16 out of 200, null probability 0.06
X-squared = 1.086, df = 1, p-value = 0.2974
alternative hypothesis: true p is not equal to 0.06
95 percent confidence interval:
 0.04790261 0.12894742
sample estimates:
   p
0.08

> prop.test(20,200,p=.06,correct=1)

	1-sample proportions test with continuity correction

data:  20 out of 200, null probability 0.06
X-squared = 4.9867, df = 1, p-value = 0.02554
alternative hypothesis: true p is not equal to 0.06
95 percent confidence interval:
 0.06366294 0.15229666
sample estimates:
  p
0.1

> # machine parts example
> prop.test(54,200,p=.35,correct=1)

	1-sample proportions test with continuity correction

data:  54 out of 200, null probability 0.35
X-squared = 5.2802, df = 1, p-value = 0.02157
alternative hypothesis: true p is not equal to 0.35
95 percent confidence interval:
 0.2109568 0.3380601
sample estimates:
   p
0.27

> # Mendel's flower color experiment
> prop.test(705,929,p=.75,correct=1)

	1-sample proportions test with continuity correction

data:  705 out of 929, null probability 0.75
X-squared = 0.3448, df = 1, p-value = 0.5571
alternative hypothesis: true p is not equal to 0.75
95 percent confidence interval:
 0.7297867 0.7858006
sample estimates:
        p
0.7588805

>