ANOVA & Chi-Sq Tests

Score 9/10From Beau La Mont with no comment

Nominal DataIssue: We are a shoe retailer, who can set up booth at either Paragon

or Central World at BTS Entrance, and want to determine whether location affects the types of shoes women wear.

Location

Types of female shoes

Siam Paragon

Central World Totals (n)

Flat 335 262 597Flip-flop (no back strap) 226 114 340Sling back (back strap) 335 218 553High Heel 161 73 234Total (n) 1057 667 1724

Contingency Table H0: No relationship exist HA: Relationship exist Decide using 5% Type I ErrorTest Statistic : X2 =16.28 df = 3P-value: 0.1%So reject H0

In Plain English: Location and type of female shoes are interdependent.

Column Distribution Location

Types of female shoes Siam Paragon Central WorldFlat 31.69347209 39.28035982

Flipflop (backstrap) 21.38126774 17.09145427

Slingback (backstrap) 31.69347209 32.68365817High Heel 15.23178808 10.94452774Prob 100 100

Flat and slingback are most worn in Paragon while in Central World, flat is most worn.

Interval Data – ANOVA Block DesignIssue: We are a fitness branch and want to determine a

higher fee for group that uses longer hours.Contingency Data

H0: u1 = u2 = u3 = u4

HA: Not all EqualDecide using 5% Type I ErrorTest Statistic : F = 0.74, df = 3,18P-Value: 74.1%We do not reject H0

In Plain English: Age groups do not affect the number of hours individuals stay at the fitness center.

Age Group

Frequencies ≤15 16 - 25 26 - 35 >35Mean Average

of BlocksBlock 1 6 3 3 3 3.75Block 2 2 4 2 3 2.75Block 3 4 1 3 5 3.25Block 4 5 5 5 4 4.75Block 5 4 4 7 4 4.75Block 6 2 2 5 5 3.5Block 7 1 4 3 3 2.75

Mean Average of Treatments 3.42 3.28 4 3.85 3.64

Collecting Nominal Data: Collecting Interval Data:

Mobile Women Shoe Shop(Nominal Data)

Fitness Center ( Piyarom Sport Club, BTS Punnawithi) (Interval Data)