Fluent Essays

One of the skills a good researcher must have is the ability to interpret data (whether qualitative or quantitative) accurately.  As a good researcher, what is the difference between correlation and causation?  Provide some examples in your answer QUANTITATIVE RESEARCH METHODOLOGIES Descriptive Research Chapter Eight What is Descriptive Quantitative Research?  This general category of research designs involves either identifying the characteristics of an observed phenomenon or exploring the possible associations among two or more phenomena.  In every case, descriptive research examines a situation as it is. Descriptive Research Designs All of these studies yield quantitative information that can be summarized through statistical analyses.  Observation Studies  Correlational Research  Developmental Designs  Survey Research Observation Studies  In quantitative research, observation studies are different than observations in qualitative research  An observation study does not necessarily involve members of the animal kingdom  A quantified observation study tends to have a particular, pre specified focus  When humans are the object, the behavior is quantified in some way – behavior may be counted to determine its overall frequency  In some situations, behavior is rated  The researcher strives to be as objective as possible Observation Studies  Strategies to maintain objectivity:  Define the behavior precisely and concretely  Divide the observation period into small segments  Use a rating scale to evaluate the behavior  Have two or three people rate the same behavior independently  Train the rater(s) to use specific criteria when counting or evaluating Correlational Research  A correlational study examines the extent to which differences in one characteristic or variable are related to differences in one or more other variables  A correlation exists if, when one variable increases, another variable increases or decreases in a somewhat predictable fashion  Researchers gather data about two or more characteristics for a particular group of people or other appropriate units of study Correlational Research  Whatever the nature of the data, at least two different characteristics are measured in order to determine whether and in what way these characteristics are interrelated  A scatter plot may be used to allow a visual inspection of the relationship between two variables  The scatter plot allows us to describe the homogeneity or heterogeneity of variables  It also allows us to describe the degree to which the two variables are intercorrelated, perhaps by computing a statistic known as a correlation coefficient  It allows us to interpret data and give them meaning Correlational Data - Caution  In all correlational studies, be alert for faulty logic  We can never infer a cause-and-effect relationship on the basis of correlation alone  Correlation does not, in and of itself, indicate causation  A way to explore the dynamics beneath the correlation is through a statistical procedure called structural equation modeling (SEM)  Another way is to follow up a correlational study with one or more experimental studies to test various hypotheses about what causes what Developmental Designs  There are two types of Developmental Designs  A cross-sectional study, wherein people from several different age-groups are sampled and compared  A longitudinal study, wherein a single group of people is followed over the course of several months or years, and data related to the characteristic(s) under investigation are collected at various times Developmental Designs  When longitudinal studies are also correlational studies, they enable researchers to identify potential mediating and moderating variables in correlational relationships  A mediating variable (intervening variable) may help explain why a characteristic is correlated with another characteristic  A moderating variable influences the nature and strength of a correlational relationship  A statistical analysis such as structural equation modeling (SEM) can be helpful for identifying mediating and moderating variables in a longitudinal study  Correlational studies cannot conclusively demonstrate cause-and-effect relationships Developmental Designs  Cross-sectional studies are easier and more expedient to conduct than longitudinal studies because the researcher can collect all the needed data at a single time  Disadvantages of cross-sectional studies  Different age groups sampled may have been raised under different environmental conditions  We cannot compute correlations between characteristics at different age levels Developmental Designs  To address some of the weaknesses of longitudinal and cross-sectional designs, researchers occasionally combine both approaches in what is known as a cohort-sequential study  Cross-sectional, longitudinal, and cohort-sequential designs are used in a variety of disciplines, but are most commonly seen in developmental research studies Survey Research  Survey research involves acquiring information about one or more groups of people by asking them questions and tabulating their answers  The ultimate goal is to learn about a large population by surveying a sample of that population; thus, this approach might be called a descriptive survey or normative survey Survey Research  A survey is simple in design; however, survey design makes critical demands on the researcher  Survey research  Captures a moment in time  Relies on self-reporting of data (by individuals)  May employ  Face-to-face interviews  Telephone interviews  Written questionnaire Planning for Data Collection in a Descriptive Study  In quantitative research, a descriptive study invariable involves measuring one or more variables in some way  Consider the distinction between substantial and insubstantial phenomena  Many descriptive studies address complex variables using a variety of strategies  Checklist  Rating scale/Likert scale Choosing a Sample in a Descriptive Study  A researcher will usually not study an entire population – instead, he or she will select a subset, or sample, of the population  The researcher can use the results obtained from the sample to make generalizations about the entire population only if the sample is truly representative of the population Sampling Designs Two categories of sampling: Probability Sampling and Non- Probability Sampling  Probability sampling Simple random sampling Stratified random sampling Proportional stratified sampling Cluster sampling Systematic sampling Sampling Designs Two categories of sampling: Probability Sampling and Non Probability Sampling  Nonprobability Sampling  Quota sampling  Purposive sampling Sampling Surveys of Large Populations  The sample must be representative of the population about which inferences are to be made  Random does not mean haphazard Identifying a Sufficient Sample Size  The larger the sample size, the better  The sample size is referred to by the symbol N  Guidelines  For smaller populations, say, N=100 or fewer, survey the entire population  If N is around 500, 50% should be sampled  If N is around 1500, 20% should be sampled  If N=5000, a sample size of 100 should be adequate Bias in Research Sampling  Bias is any influence, condition, or set of conditions that singly or in combination distort the data  Bias attacks the integrity of the facts  Report response rate Acknowledging the Probable Presence of Bias  When formulating conclusions about the data, a researcher must be sure to consider the effect that bias may have had in distorting the data Interpreting Data in Descriptive Research  There is more to research than data collection  All research activity is subordinate to the research problem itself  Two basic principles of research  Seek the answer to a problem in light of the data that relate to the problem  Interpretation of the data is all-important