Two sample proportion confidence interval:

p₁ : Proportion of successes (Success = Failed) for Status where Sex = "F"
p₂ : Proportion of successes (Success = Failed) for Status where Sex = "M"
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	10	24	6	20	0.11666667	0.14362213	-0.16482753	0.39816086

Two sample proportion confidence interval:

p₁ : Proportion of successes (Success = Failed) for Status where Section = "A"
p₂ : Proportion of successes (Success = Failed) for Status where Section = "B"
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	8	22	8	22	0	0.14504073	-0.28427461	0.28427461

Two sample proportion confidence interval:

p₁ : Proportion of successes (Success = yes) for planner
p₂ : Proportion of successes (Success = male) for gender
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	31	50	11	50	0.4	0.090244113	0.22312479	0.57687521

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0.05
H_A : p₁ - p₂ ≠ 0.05

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	242	300	57	300	0.61666667	0.040824602	13.880519	<0.0001

Two sample proportion summary confidence interval:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	87	100	13	100	0.74	0.047560488	0.64678316	0.83321684

Two sample proportion hypothesis test:

p₁ : Proportion of successes (Success = 5890) for AGE
p₂ : Proportion of successes (Success = 3142) for PLATE
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 1
H_A : p₁ - p₂ ≠ 1

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	0	300	0	300	0	0	NaN	NaN

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ ≠ 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	480	1022	514	1008	-0.040253316	0.022190615	-1.8139793	0.0697

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ > 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	210	450	102	305	0.13224044	0.036521576	3.6208853	0.0001

Two sample proportion summary confidence interval:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions

90% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	660	800	440	700	0.19642857	0.02267149	0.15913729	0.23371985

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ ≠ 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	24	30	17	38	0.35263158	0.11949973	2.9508985	0.0032

Two sample proportion summary confidence interval:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	51	70	53	80	0.066071429	0.074966624	-0.080860455	0.21300331

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ ≠ 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	51	70	53	80	0.066071429	0.075466801	0.87550323	0.3813

Two sample proportion summary hypothesis test:

p₁ : proportion of successes for population 1
p₂ : proportion of successes for population 2
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ ≠ 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	14	152	12	449	0.065379205	0.019091427	3.4245321	0.0006

Two sample proportion hypothesis test:

p₁ : Proportion of successes (Success = In store) for Sample(Shoes and Clothing - Online or Store) where "Sample(Future of Shopping)" = "No"
p₂ : Proportion of successes (Success = In store) for Sample(Shoes and Clothing - Online or Store) where "Sample(Future of Shopping)" = "Yes"
p₁ - p₂ : Difference in proportions
H₀ : p₁ - p₂ = 0
H_A : p₁ - p₂ ≠ 0

Hypothesis test results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1 - p2	64	77	50	73	0.14623732	0.069767194	2.0960758	0.0361

Two sample proportion confidence interval:

p₁ : Proportion of successes (Success = In store) for Sample(Shoes and Clothing - Online or Store) where "Sample(Future of Shopping)" = "No"
p₂ : Proportion of successes (Success = In store) for Sample(Shoes and Clothing - Online or Store) where "Sample(Future of Shopping)" = "Yes"
p₁ - p₂ : Difference in proportions

95% confidence interval results:

Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	L. Limit	U. Limit
p1 - p2	64	77	50	73	0.14623732	0.06912742	0.01075007	0.28172458