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1-11-1

by by

Marc M. Triola & Mario F. TriolaMarc M. Triola & Mario F. Triola

SLIDES PREPARED BY SLIDES PREPARED BY

LLOYD R. JAISINGHLLOYD R. JAISINGH

MOREHEAD STATE UNIVERSITYMOREHEAD STATE UNIVERSITY

MOREHEAD KYMOREHEAD KY

(with modifications by DGE Robertson)(with modifications by DGE Robertson)

Biostatistics Biostatistics for the Biological and Health

Sciences

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Chapter 1Chapter 1

IntroductionIntroduction

WCB/McGraw-Hill

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1-31-3 OutlineOutline

1-1 Introduction 1-2 Types of Data 1-4 Data Collection and Data Collection and

Sampling Techniques Sampling Techniques 1-5 Computers and Calculators

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1-51-5 ObjectivesObjectives

Demonstrate knowledge of all statistical terms.

Differentiate between the two branches of statistics.

Identify types of data.

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1-61-6 ObjectivesObjectives

Identify the measurement level for each variable.

Identify the four basic sampling techniques.

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1-81-8 1-1 Introduction1-1 Introduction

StatisticsStatistics consists of conducting studies to collect, organize, summarize and analyze data and to draw conclusions

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1-91-91-1 Descriptive and Inferential 1-1 Descriptive and Inferential

StatisticsStatistics

DataData are the values (measurements or observations) that the variables can assume.

Variables whose values are determined by chance are called random variablesrandom variables.

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StatisticsStatistics

A collection of data values forms a data set.data set.

Each value in the data set is called a data valuedata value or a datumdatum.

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1-111-111-1 Descriptive and Inferential 1-1 Descriptive and Inferential

StatisticsStatistics

Descriptive statisticsDescriptive statistics consists of the collection, organization, summation and presentation of data.

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StatisticsStatistics

A populationpopulation consists of all subjects (human or otherwise) that are being studied.

A samplesample is a subgroup of the population.

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1-131-131-1 Descriptive and Inferential 1-1 Descriptive and Inferential

StatisticsStatistics

Inferential statisticsInferential statistics consists of generalizing from samples to populations, performing hypothesis testing, determining relationships among variables, and making predictions.

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1-141-14 1-2 Variables and Types of Data1-2 Variables and Types of Data

Qualitative variablesQualitative variables are variables that can be placed into distinct categories, according to some characteristic or attribute. For example, gender (male or female).

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Quantitative variablesQuantitative variables are numerical in nature and can be ordered or ranked. Example: age is numerical and the values can be ranked.

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1-161-16 1-2 Variables and Types of Data1-2 Variables and Types of Data

Discrete variablesDiscrete variables assume values that can be counted.

Continuous variablesContinuous variables can assume all values between any two specific values. They are obtained by measuring.

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1-171-17 1-2 Variables and Types of Data1-2 Variables and Types of Data

The nominal level of measurementnominal level of measurement classifies data into mutually exclusive (nonoverlapping), exhausting categories in which no order or ranking can be imposed on the data.

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1-181-18 1-2 Variables and Types of Data1-2 Variables and Types of Data

The ordinal level of measurementordinal level of measurement classifies data into categories that can be ranked; precise differences between the ranks do not exist.

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The interval level of measurementinterval level of measurement ranks data; precise differences between units of measure do exist; there is no meaningful zero.

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1-201-201-2 Types of Data1-2 Types of Data

The ratio level of measurementratio level of measurement possesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist for the same variable.

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1-211-211-4 Data Collection and Sampling 1-4 Data Collection and Sampling Techniques Techniques

Data can be collected in a variety of ways. One of the most common methods is

through the use of surveys. Surveys can be done by using a variety of

methods: Examples are telephone, mail questionnaires,

personal interviews, surveying records and direct observations.

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1-221-221-4 Data Collection and Sampling 1-4 Data Collection and Sampling Techniques Techniques

To obtain samples that are unbiased, statisticians use four methods of sampling.

Random samplesRandom samples are selected by using chance methods or random numbers.

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Systematic samplesSystematic samples are obtained by numbering each value in the population and then selecting the kth value.

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Stratified samplesStratified samples are selected by dividing the population into groups (strata) according to some characteristic and then taking samples from each group.

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Cluster samplesCluster samples are selected by dividing the population into groups and then taking samples of the groups.

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1-251-251-4 Data Collection and Sampling 1-4 Data Collection and Sampling Techniques Techniques

Convenience samplesConvenience samples are when subjects are selected for convenience. (Often used in student research projects or by advertisers.)

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1-261-26 1-5 Calculators 1-5 Calculators

Calculators make some statistical tests and numerical computations easier.

The TI-35 and TI-83 calculators perform 2-variable statistical calculations.

Must learn how to enter and perform statistical functions on your calculator.

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1-261-261-5 Computers and Calculators 1-5 Computers and Calculators

Computers can perform more advanced statistical tests.

Many statistical packages are available. Examples are SPSS, SAS and MINITAB also Excel and QuattroPro.

Input and output from computer must understood and interpreted.