250 Introduction to Biostatistics Kari Lock Morgan klm47psuedu Biology Education Core Competencies Vision and Change 2011 1 Ability to apply the process of science Biology is ID: 433128
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Slide1
STAT 250: Introduction to Biostatistics
Kari Lock Morgan
klm47@psu.edu
Slide2
Biology Education Core Competencies(Vision and Change, 2011)1. Ability to apply the process of science: Biology is
evidence based
and grounded in the formal practices of
observation
,
experimentation
, and
hypothesis testing
.
2.
Ability to use
quantitative reasoning
:
Biology relies on applications of
quantitative analysis
and
mathematical reasoning
3.
Ability to use
modeling
and
simulation
(plus 3 more…)Slide3
www.personal.psu.edu/klm47/Courses/STAT250/Spring2015/schedule.html
Lecture slides and course documents will be posted here
Course Website
SyllabusSlide4
Course MaterialsStatistics: Unlocking the Power of Databy Lock, Lock, Lock Morgan, Lock, and Lock*Purchase with WileyPlus
Purchasing options
Why
WileyPlus
?
Get iclicker or iclicker+ Register by 1/23/15 at clickers.psu.edu Slide5
Keys to SuccessCome to class ready to think and be engagedCome to lab ready to think and be engagedDo the homework and give it an honest effortDo lots of practice problemsRead the textbook or watch videosStay on top of the materialSlide6
Introduction to DataSECTION 1.1
Data
Cases and variables
Categorical and quantitative variables
Explanatory and response Variables
Using data to answer a questionSlide7
Why Statistics?Statistics is all about DATACollecting DATADescribing DATA – summarizing, visualizing Analyzing DATAData are everywhere! You will have to make decisions based on data, or evaluate decisions someone else has made based on data
(This is
particularly
true in the health sciences!)Slide8
DataData are a set of measurements taken on a set of individual unitsUsually data is stored and presented in a dataset, comprised of variables measured on casesSlide9
Cases and VariablesWe obtain information about cases or units.A variable is any characteristic that is recorded for each case.
Generally each case makes up a row in a dataset, and each variable makes up a columnSlide10
National Health and Nutrition Examination Survey Slide11
Countries of the WorldCountry
Land Area
Population
Rural
Health
InternetBirth RateLife ExpectancyHIV
Afghanistan
65223029021099
76
3.7
1.7
46.5
43.9
Albania
27400
3143291
53.3
8.2
23.9
14.6
76.6
Algeria
2381740
34373426
34.8
10.6
10.2
20.8
72.4
0.1
American Samoa
200
66107
7.7
Andorra
470
83810
11.1
21.3
70.5
10.4
Angola
1246700
18020668
43.3
6.8
3.1
42.9
47
2
Antigua and Barbuda
440
86634
69.5
11
75
Argentina
2736690
39882980
8
13.7
28.1
17.3
75.3
0.5Slide12
Diet Coke and Calcium
Drink
Calcium Excreted
Diet cola
50
Diet cola62Diet cola48Diet cola55
Diet cola
58Diet cola
61
Diet cola
58
Diet cola
56
Water
48
Water
46
Water
54
Water
45
Water
53
Water
46
Water
53
Water
48Slide13Slide14
Data Applicable to YouThink of a potential dataset (it doesn’t have to actually exist) that you would be interested in analyzingWhat are the cases?What are the variables?What interesting questions could it help you answer?Slide15
Kidney CancerSource: Gelman et. al. Bayesian Data Anaylsis, CRC Press, 2004.
Counties with the highest
kidney cancer death ratesSlide16
Kidney CancerIf the values in the kidney cancer dataset are rates of kidney cancer deaths, then what are the cases? The people living in the US The counties of the USSlide17
Kidney CancerIf the values in the kidney cancer dataset are yes/no, then what are the cases? The people living in the US The counties of the USSlide18
Categorical versus QuantitativeA categorical variable divides the cases into groupsA quantitative variable measures a numerical quantity for each case
Variables are classified as either
categorical
or
quantitative
:Slide19Slide20
Kidney CancerIf the cases in the kidney cancer dataset are counties, then the measured variable is… Categorical QuantitativeSlide21
Kidney CancerIf the cases in the kidney cancer dataset are people, then the measured variable is… Categorical QuantitativeSlide22
Explanatory and ResponseIf we are using one variable to help us understand or predict values of another variable, we call the former the explanatory variable and the latter the response variableExamples:
Does meditation help reduce stress?
Does sugar consumption increase hyperactivity?Slide23
VariablesFor each of the following situations: What are the variables? Is each variable categorical or quantitative? Identify the explanatory and response variables.Are
children with higher exposure to pesticides more likely to develop ADHD?
Does exercise make you smarter?
Can dogs detect cancer?
Do males find females more attractive if they wear red?
(We’ll explore all of these questions during the course!) Slide24
SummaryData are everywhere, and pertain to a wide variety of topicsA dataset is usually comprised of variables measured on casesVariables are either categorical or quantitativeData can be used to provide information about essentially anything we are interested in and want to collect data on!Slide25
To DoRead Section 1.1Due Friday, 1/16: Take the two pretestsPretest 1Pretest 2Due Friday, 1/23: Section 1.1 HWIf you haven’t already…Get the textbook with WileyPlusGet a clicker and register it on ANGEL
by 1/23Slide26
Why Statistics?http://www.youtube.com/watch?v=nTBZuQR7dRc&feature=youtu.be