1 / 26

460 likes | 987 Views

Biostatistics for the Biological and Health Sciences. 1-1. by Marc M. Triola & Mario F. Triola SLIDES PREPARED BY LLOYD R. JAISINGH MOREHEAD STATE UNIVERSITY MOREHEAD KY (with modifications by DGE Robertson). Chapter 1. 1-2. Introduction. WCB/McGraw-Hill.

Download Presentation
## 1-1

**An Image/Link below is provided (as is) to download presentation**
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.
Content is provided to you AS IS for your information and personal use only.
Download presentation by click this link.
While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

**Biostatistics**for the Biological and Health Sciences 1-1 by Marc M. Triola & Mario F. Triola SLIDES PREPARED BY LLOYD R. JAISINGH MOREHEAD STATE UNIVERSITY MOREHEAD KY (with modifications by DGE Robertson)**Chapter 1**1-2 Introduction WCB/McGraw-Hill • The McGraw-Hill Companies, Inc., 1998**Outline**1-3 • 1-1 Introduction • 1-2 Types of Data • 1-4 Data Collection and Sampling Techniques • 1-5 Computers and Calculators**Objectives**1-5 • Demonstrate knowledge of all statistical terms. • Differentiate between the two branches of statistics. • Identify types of data.**Objectives**1-6 • Identify the measurement level for each variable. • Identify the four basic sampling techniques.**1-1 Introduction**1-8 • Statisticsconsists of conducting studies to collect, organize, summarize and analyze data and to draw conclusions**1-1 Descriptive and Inferential Statistics**1-9 • Dataare the values (measurements or observations) that the variables can assume. • Variables whose values are determined by chance are called random variables.**1-1 Descriptive and Inferential Statistics**1-10 • A collection of data values forms a data set. • Each value in the data set is called a data value or a datum.**1-1 Descriptive and Inferential Statistics**1-11 • Descriptive statistics consists of the collection, organization, summation and presentation of data.**1-1 Descriptive and Inferential Statistics**1-12 • A population consists of all subjects (human or otherwise) that are being studied. • A sampleis a subgroup of the population.**1-1 Descriptive and Inferential Statistics**1-13 • Inferential statistics consists of generalizing from samples to populations, performing hypothesis testing, determining relationships among variables, and making predictions.**1-2 Variables and Types of Data**1-14 • Qualitative variablesare variables that can be placed into distinct categories, according to some characteristic or attribute. For example, gender (male or female).**1-2 Variables and Types of Data**1-15 • Quantitative variablesare numerical in nature and can be ordered or ranked. Example: age is numerical and the values can be ranked.**1-2 Variables and Types of Data**1-16 • Discrete variablesassume values that can be counted. • Continuous variablescan assume all values between any two specific values. They are obtained by measuring.**1-2 Variables and Types of Data**1-17 • Thenominal level of measurementclassifies data into mutually exclusive (nonoverlapping), exhausting categories in which no order or ranking can be imposed on the data.**1-2 Variables and Types of Data**1-18 • Theordinal level of measurementclassifies data into categories that can be ranked; precise differences between the ranks do not exist.**1-2 Variables and Types of Data**1-19 • Theinterval level of measurementranks data; precise differences between units of measure do exist; there is no meaningful zero.**1-2 Types of Data**1-20 • Theratio level of measurementpossesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist for the same variable.**1-4 Data Collection and Sampling Techniques**1-21 • 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.**1-4 Data Collection and Sampling Techniques**1-22 • To obtain samples that are unbiased, statisticians use four methods of sampling. • Random samplesare selected by using chance methods or random numbers.**1-4 Data Collection and Sampling Techniques**1-23 • Systematic samplesare obtained by numbering each value in the population and then selecting the kth value.**1-4 Data Collection and Sampling Techniques**1-24 • Stratified samplesare selected by dividing the population into groups (strata) according to some characteristic and then taking samples from each group.**1-4 Data Collection and Sampling Techniques**1-25 • Cluster samplesare selected by dividing the population into groups and then taking samples of the groups.**1-4 Data Collection and Sampling Techniques**1-25 • Convenience samplesare when subjects are selected for convenience. (Often used in student research projects or by advertisers.)**1-5 Calculators**1-26 • 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.**1-5 Computers and Calculators**1-26 • 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.

More Related