1. Unit 2 Special centers; Trimmed & Weighted Mean

2. Let’s look at some data How Fast Food Compare Company Fast FoodTotalFatCholesterolSodium Calories(g)(mg) Kentucky Fried Chicken Lite 'n Crispy (4 pieces)1981239354 Burger King Hamburger Deluxe3441955496 Wendy's Single (plain)3401550500 Kentucky Fried Chicken Original Recipe (4pieces)2481539575 McDonald's Chicken McNuggets (6)2701542580 Arby's Regular Roast Beef3531556588 Kentucky Fried Chicken Extra Crispy (4 pieces)3242147638 McDonald's Quarter Pounder4102060650 McDonald's McLean Deluxe3201047670 Arby's French Dip3451255678 Wendy's Chicken (regular)4301970725 Hardee's Big Deluxe Burger5003079760 Burger King BK Broiler Chicken3791860764 McDonald's McChicken4152065770 Comparing various fast food components of nutrition. Calories Fat Cholesterol Sodium

3. The Mean grams of Fat in the fast foods Fat (g) 915 192429 1015 192530 1215 202533 121516202636 131618202840 1318 212961

4. The Trimmed Mean Fat (g) 915 192429 1015 192530 1215 202533 121516202636 131618202840 1318 212961 Do you notice that one particular value is possibly an outlier. In order to better compute a “truer” average we will use a “Trimmed” mean.

5. The Trimmed Mean The trimmed mean has the advantage of being relatively resistant to outliers. The trimmed mean is computed just as an ordinary mean...except. a pre-specified percentage of the extremes is omitted. Consider the 5% trimmed mean. The left-most (lowest) 5% and right-most (highest) 5% of the data are excluded; from the remaining observations the mean is found. So, the 10% most "extreme" data (5% on either side) is omitted before computing the mean.

6. Trimmed Mean Fat (g) 915 192429 1015 192530 1215 202533 121516202636 131618202840 1318 212961 5% Trim Drop the 2 smallest & 2 largest values

7. The Trimmed Mean Fat (g) 915 192429 1015 192530 1215 202533 121516202636 131618202840 1318 212961

8. The Trimmed Mean – you try it Fat (g) 3950607090 3953607090 4255607090 4355607999 47566082100 47576585194

9. The Weighted Mean weighted mean  The weighted mean is used when the values in a data set are not all equally represented. weighted meanof a variable X  The weighted mean of a variable X is found by multiplying each value by its corresponding weight and dividing the sum of the products by the sum of the weights.

10. The Weighted Mean

11. Cost of Shoes ($) ShoeCost No. Sold Air Jordan$1403 KD$1354 Kobe$2001 Air Force$855 Converse$459

12. The Weighted Mean- using the table Cost of Shoes ($) Shoe Cost (x) No. Sold ( w ) wxwx Air Jordan$1403$420 KD$1354$540 Kobe$2001 Air Force$855$425 Converse$459$405 totals22$ 1990