Distribution

Question 1

Simple descriptive stats
* Mean (Average):
* Median:
* Mode:
* Range:
* Variance:
* Standard Deviation:

Answer 1

• Mean (Average): The sum of all values divided by the number of values.
• Median: The middle value when all values are arranged in ascending or descending order. If there’s an even number of observations, it is the average of the two middle numbers.
• Mode: The value that appears most frequently in the data set.
• Range: The difference between the highest and lowest values in the data set.
• Variance: The average of the squared differences from the Mean. It measures how spread out the values are.
• Standard Deviation: The square root of the variance,
  representing the dispersion of the dataset relative to its mean.
• ~68% of the data is incorporated in the standard deviation

Question 2

Question 3

Stats are generally good but why don’ they apply to me?
* Law of …
* 30+ sample sizes = we can use the stats.
* Problems with large numbers…
* A one in a million occurrence happens 10x a
week in Calgary….
* In the included graph, the body weight of
the athletic population and obese
populations crosses at less than 2%. Why
would dietary strategies that have been
proven in one population be applied to the
other?

STANDARD ERROR = …

Answer 3

• Law of large number….
• 30+ sample sizes = we can use the stats.
• Problems with large numbers…
• A one in a million occurrence happens 10x a
  week in Calgary….
• In the included graph, the body weight of
  the athletic population and obese
  populations crosses at less than 2%. Why
  would dietary strategies that have been
  proven in one population be applied to the
  other?

STANDARD ERROR = standard deviation / sample size^-2

Question 4

How odd is knickers…

The average steer height in
Australia is:

1.25 meters at the shoulder - 600 Kg
.25 m or 25 cm Standard Dev. - 150 Kg

Knickers is ~ 2.0 m
And ~ 1500 Kg

Question 5

what are the x and 6

Answer 5

Question 6

Question 7

Definition of a z-score
Z-scores:
* Are expressed in terms of….
* Are a measure of how many standard deviations a raw score is….
* Have a distribution with a mean of … and a standard deviation of …

Answer 7

Definition of a z-score
Z-scores:
* Are expressed in terms of standard deviations from their means.
* Are a measure of how many standard deviations a raw score is below or above the population mean.
* Have a distribution with a mean of 0 and a standard deviation of 1.

Question 8

Question 9

Answer 9

species of lobster

knickers is much older than the rest

Question 10

Assumptions of a z-score
* Need … or … data (…)
* Need to know the population … & …
* We assume that the data we are examining comes
from a…
* If the sample size is …, a z-score may not be
appropriate

Purpose of a z-score
* Standardize a group of…
* Compare scores from a … to a
normal distribution.
* Standardize a group of…

!!!!!!!
* Z- scores underline the importance of considering
variance or the standard deviation when understanding
a score.
* Because everything is normalized to 1 standard
deviation, with a z-score we can literally compare apples and oranges if we want

Answer 10

Assumptions of a z-score
* Need interval or ratio data (continuous variables, NOT DISCRETE)
* Need to know the population mean & variance
* We assume that the data we are examining comes
from a normally distributed population
* If the sample size is small, a z-score may not be
appropriate

Purpose of a z-score
* Standardize a group of scores
* Compare scores from a measure/test to a
normal distribution.
* Standardize a group of variables for
comparison

Question 11

Question 12

What is significance?
* T scores are very similar to z scores but are for…

• A result has statistical significance when we see
  differences… (reject …)

two different graphs

Answer 12

• T scores are very similar to z scores but are for groups…
• A result has statistical significance when we see
  differences in the mean. (reject the null hypothesis.)

THEY OVERLAP, MOST OF THE PEOPLE DID NOT SHIFT
THEY ARE IN THE SAME VALUES AS THE PREVIOUS ONE
NOT MUCH DIFFERENCE

Question 13

• Alpha levels establish …
• Recorded score = …
• Error = …

Answer 13

• Alpha levels establish a likelihood of seeing a difference, when considering the error for a given measurement instrument
• Recorded score = true score + error
• Error = confounding variability in the measure

Question 14

• Your chosen alpha dictates your p value.
• α = 0.05 = 1/20 = Z-score of
• p< 0.05 =
• p< 0.01 =
• p< 0.001 =

Answer 14

Question 15

as sample size increases, standard deviation …

Answer 15

as sample size increases, standard deviation decreases