Week 2 - General Types of Quantitative Research PDF

General Types of Quantitative Research and Designs Prayer Week 2- August 5-6, 2024 "BASTA TRADEAN, magaling at maaasahan!"  Practical Research 2 By Cromwell F. Gopo Research 2 Learning Objectives  Research 2 Learning Objectives At...

General Types of Quantitative Research and Designs Prayer Week 2- August 5-6, 2024 "BASTA TRADEAN, magaling at maaasahan!"  Practical Research 2 By Cromwell F. Gopo Research 2 Learning Objectives  Research 2 Learning Objectives At the end of the lesson, students will be able to: determine the research type using the definition given; and match the different situations to the presented research designs. Opening Activity Identifying the Features of Your Phone Research 2 Activity 1 Determining the Research Type Using the Definition Given Research 2 What research is this? It controls for both time-related and group-related threats. It offers the highest internal validity of all the designs. Research 2 What research is this? It controls for both time-related and group-related threats. It offers the highest internal validity of all the designs. EXPERIMENTAL  Research 2 What research is this? It is used when the researcher intends to provide a quantitative or numeric description of trends, attitudes, or opinions of a population. It may be done in various ways like face-to-face, phone, mail and online. Research 2 What research is this? It is used when the researcher intends to provide a quantitative or numeric description of trends, attitudes, or opinions of a population. It may be done in various ways like face-to-face, phone, mail and online. SURVEY Research 2 What research is this? All variables in the study can contribute to the overall prediction in an equation that adds together the predictive power of each identified variable. Research 2 What research is this? All variables in the study can contribute to the overall prediction in an equation that adds together the predictive power of each identified variable. DESCRIPTIVE-CORRELATIONAL  Research 2 What research is this? It involves comparing and contrasting two or more samples of study subjects on one or more variables, often at a single point of time. Research 2 What research is this? It involves comparing and contrasting two or more samples of study subjects on one or more variables, often at a single point of time. COMPARATIVE Research 2 What research is this? It seeks to assess the effects, impacts or outcome of practices, policies, or programs. Research 2 What research is this? It seeks to assess the effects, impacts or outcome of practices, policies, or programs. EVALUATIVE Activity 2 Matching the Titles with the Different Research Designs Research 2 What design is this? Flipping the calculus classroom: An evaluative study Research 2 What design is this? Flipping the calculus classroom: An evaluative study EVALUATIVE Research 2 What design is this? Use of Smartphone and School Engagement of Students Research 2 What design is this? Use of Smartphone and School Engagement of Students DESCRIPTIVE-CORRELATIONAL Research 2 What design is this? Effectiveness of collaborative learning among gen z engineering students Research 2 What design is this? Effectiveness of collaborative learning among gen z engineering students EXPERIMENTAL Discussing the Types of Quantitative Research and Designs Research 2 Types of Quantitative Research Non- Experimental Experimental Types Experimental Research  Research 2 Experimental Research A true experimental design is one in which study participants are randomly assigned to experimental and control groups.  Research 2 Experimental Research Regardless of the technique used to randomly assign participants to groups within a study, random assignment increases the likelihood that changes in the dependent variable are attributable to the independent variables rather than to extraneous factors or nuisance variables. Research 2 Experimental Research True Experimental Research Quasi-Experimental Research Pre-experimental Research  Research 2 Experimental Research Legend: X = experimental manipulation (independent variable); subscripts identify different levels or groups of the independent variable (e.g., X1, X2 , X3 is used to denote either a nointervention or alternative-intervention control group) Y = experimental manipulation (independent variable) other than X O = observation R = indication that participants have been randomly assigned NR = indication that participants have not been randomly assigned Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design The primary purpose of this design is to demonstrate causality— that is, to determine whether a specific intervention (the independent variable) causes an effect (as opposed to being merely correlated with an effect). Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design For example, a researcher studying smoking cessation may randomly assign identified cigarette smokers either to a novel medication (experimental) group or to a comparison (control) group. Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design a. Randomized Two-Group Posttest Only Design In its most basic form, the two-group experimental design may involve little more than random assignment and a posttest, as depicted here: Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design a.Randomized Two-Group Posttest Only Design This simple design encompasses all the necessary elements of a true randomized experiment: (1) random assignment, to distribute extraneous differences across groups; (2) intervention and control groups, to determine whether the treatment had an effect; and (3) observations following the treatment. Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design b. Randomized Two-Group Pretest-Posttest Design Despite the relative simplicity of the posttest only approach, most randomized experiments typically utilize the pretest-posttest design, which is depicted here: Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design b. Randomized Two-Group Pretest-Posttest Design It allows the researcher to compare the groups on several measures following randomization to determine whether the groups are truly equivalent. It provides baseline information that allows researchers to compare the participants who completed the posttest to those who did not. Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design b.Randomized Two-Group Pretest-Posttest Design Despite this drawback, the two-group experimental design may be seen as the gold standard in determining whether a new procedure (or independent variable) causes an effect. Research 2 Experimental Research: True Experimental Research Designs 1. Randomized Two-Group Design b.Randomized Two-Group Pretest-Posttest Design Researchers often employ this design in the early stages of an intervention’s empirical validation. At these initial stages, the researcher’s primary aim may simply be to examine the effectiveness of the intervention. Research 2 Experimental Research: True Experimental Research Designs 2. Solomon Four-Group Design It is perhaps easiest to understand the Solomon four-group design if we think of it as a combination of the randomized posttest only and pretest-posttest two-group designs, as depicted below: Research 2 Experimental Research: True Experimental Research Designs 2. Solomon Four-Group Design The principal advantage of this design is that it controls for the potential effects of the pretest on posttest outcomes. This design allows the researcher to determine whether posttest differences resulted from the intervention, the pretest, or a combination of the treatment and the pretest. Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design Most outcomes in research are likely to have several causes that interact with each other in a variety of ways that cannot be identified through the use of two-group experimental designs. The Solomon four-group design, which may also be viewed as a factorial design, was able to control for this potential interaction. Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design The primary advantage of factorial designs is that they enable us to empirically examine the effects of more than one independent variable, both individually and in combination, on the dependent variable. Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design The design, as its name implies, allows us to examine all possible combinations of factors in the study: Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design To further illustrate the utility of this design, let us consider a situation in which a researcher is interested in examining how both treatment dose (4 vs. 8 sessions) and treatment setting (client’s home vs. clinical setting) influence the effectiveness of a particular intervention. Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design Although the researcher could conduct separate two- group randomized studies, this would not provide information on the potential interaction of different doses of treatment with different treatment settings. The researcher might, for example, want to test the hypothesis that higher doses of treatment provided in a clinical setting will result in the best treatment outcomes. Research 2 Experimental Research: True Experimental Research Designs 3. Factorial Design This specific example would be considered a two-by two (2 × 2) factorial design, because each of the two independent variables has two levels, as illustrated here: Research 2 Experimental Research True Experimental Research 1. Randomized True Group Design *Randomized Two-Group Posttest Only Design *Randomized Two-Group Pretest-Posttest Design 2. Solomon Four-Group Design 3. Factorial Design Quasi-Experimental Research Pre-experimental Research  Research 2 Quasi-Experimental Research Regardless of the technique used to randomly assign participants to groups within a study, random assignment increases the likelihood that changes in the dependent variable are attributable to the independent variables rather than to extraneous factors or nuisance variables.  Research 2 Quasi-Experimental Research A good rule of thumb is that researchers should attempt to use the most rigorous research design possible, striving to use a randomized experimental design whenever possible (Campbell, 1969).  Research 2 Quasi-Experimental Research Cook and Campbell (1979) present a variety of quasi-experimental designs, which can be divided into two main categories: nonequivalent comparison-group designs and interrupted time-series designs. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs Nonequivalent comparison-group designs are among the most commonly used quasi- experimental designs. Structurally, these designs are quite similar to the experimental designs, but an important distinction is that they do not employ random assignment. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs In using these designs, the researcher attempts to select groups that are as similar as possible. Unfortunately, as indicated by the design’s name, it is likely that the resulting groups will be nonequivalent. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs a. Nonequivalent Groups Posttest-Only (Two or More Groups) In the nonequivalent groups posttest-only design, one group (the experimental group) receives the intervention while the other group (the control group) does not, as depicted here (NR = not randomized): Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs a. Nonequivalent Groups Posttest-Only (Two or More Groups) One potential application of this design (Cook & Campbell, 1979; McGuigan, 1983) is a case in which each of the groups might represent a different type of teaching method. If differences are found in the resulting test scores of students, it may suggest that the specific teaching method caused the differences. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs a. Nonequivalent Groups Posttest-Only (Two or More Groups) However, it is equally possible that students who were likely to achieve higher grades were selected for a specific teaching method. Ultimately, even this variation cannot rule out the serious threats to internal validity that plague this design. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs b. Nonequivalent Groups Pretest-Posttest (Two or More Groups) In the nonequivalent groups pretest-posttest design, the dependent variable is measured both before and after the treatment or intervention, as depicted here: Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs b. Nonequivalent Groups Pretest-Posttest (Two or More Groups) This gives it two advantages over its posttest only counterpart. First, with the use of both a pretest and a posttest, the temporal precedence of the independent variable to the dependent variable can be established. This may give the researcher more confidence when inferring that the independent variable was responsible for changes in the dependent variable. Research 2 Experimental Research: Quasi-Experimental Research Designs 1. Nonequivalent Comparison-Group Designs b. Nonequivalent Groups Pretest-Posttest (Two or More Groups) Second, the use of a pretest allows the researcher to measure between-group differences before exposure to the intervention. This could substantially reduce the threat of selection bias by revealing whether the groups differed on the dependent variable prior to the intervention. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs The time-series design is perhaps best described as an extension of a one group pretest-posttest design—the design is extended by the use of numerous pretests and posttests. In this type of quasi-experimental design, periodic measurements are made on a group prior to the presentation (interruption) of the intervention to establish a stable baseline. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs Observing and establishing the normal fluctuation of the dependent variable over time allows the researcher to more accurately interpret the impact of the independent variable. Following the intervention, several more periodic measurements are made. There are four basic variations of this design: the simple interrupted time-series design, the reversal time-series design, the multiple time-series design, and the longitudinal design. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs a. Simple Interrupted Time-Series Design The simple interrupted time-series design is a within-subjects design in which periodic measurements are made on a single group in an effort to establish a baseline, as depicted here: Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs a. Simple Interrupted Time-Series Design At some point in time, the independent variable is introduced, and it is followed by additional periodic measurements to determine whether a change in the dependent variable occurs. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs a. Simple Interrupted Time-Series Design According to Cook and Campbell (1979), there are two principal ways in which the independent variable can influence the series of observations after it has been introduced: (1) a change in the level and (2) a change in the slope. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs a. Simple Interrupted Time-Series Design A sharp discontinuity in the values of the dependent variable at the point of interruption (introduction of the independent variable) would indicate a change in level. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs b. Reversal Time-Series Design The basic goal of this design is to establish causality by presenting and withdrawing an intervention, or independent variable, one to several times while concurrently measuring change in the dependent variable. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs b. Reversal Time-Series Design As in the simple time-series design, this design begins with a series of pretests to observe normal fluctuations in baseline. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs b. Reversal Time-Series Design The name “reversal” refers to the idea that causality can be inferred if changes that occur following the presentation of an intervention diminish or “reverse” when the independent variable is withdrawn.  Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs b. Reversal Time-Series Design Example Imagine if, rather than offering a one-time bonus, the employer offered a monthly bonus to employees for 2 months, removed it for 2 months, and then again offered it for 2 months. If increases in productivity were found following each bonus, and decreases in productivity were found each time the bonus was removed, one could be fairly confident that company bonuses influenced employee productivity. Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs c. Multiple Time-Series Design This design is essentially the same as the nonequivalent pretest-posttest design, with the exception that the dependent variable is measured at multiple time points both before and after presentation of the independent variable, or longitudinally, as depicted here: Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs c. Multiple Time-Series Design Although this design is not randomized, it can be quite strong in terms of its ability to rule out other explanations for the observed effect. This design enables us to examine trends in the data, at multiple time points, before, during, and after an intervention (allowing us to evaluate the plausibility of certain threats to internal validity). Research 2 Experimental Research: Quasi-Experimental Research Designs 2. Interrupted Time-Series Designs c. Multiple Time-Series Design Over and above the single-group time-series design, however, this design allows us to make both within-group and between-group comparisons, which may further reduce concerns of alternative explanations associated with history. Therefore, the major strength of this design is that it permits both within and between-group comparisons. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs According to Kazdin (2003c), single-subject experiments might be seen as true experiments because they “can demonstrate causal relationships and can rule out or make implausible threats to validity with the same elegance of group research.” Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs Similar to other experimental designs, the single- subject design seeks to: (1) establish that changes in the dependent variable occur following introduction of the independent variable (temporal precedence) and (2) identify differences between study conditions. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs a. Single-Subject Reversal Design As in the reversal time-series design, the single- subject reversal design measures behavior during three phases: before the intervention is introduced (A), after introducing the intervention (B), and again after withdrawing the intervention (A). Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs a. Single-Subject Reversal Design The primary goal of this design is, first, to determine whether there is a change in the dependent variable following the introduction of the independent variable; and second, to determine whether the dependent variable reverses or returns to baseline once the independent variable is withdrawn. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs b. Single-Subject Multiple-Baseline Design This design demonstrates the effectiveness of a treatment by showing that behaviors across more than one baseline change as a consequence of the introduction of a treatment. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs b. Single-Subject Multiple-Baseline Design In this design, several behaviors of a single subject are monitored simultaneously. Once stable baselines are established for all of the behaviors, one of the behaviors is exposed to the intervention. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs b. Single-Subject Multiple-Baseline Design The primary goal of this design is to determine whether the behavior that is exposed to the intervention changes while the other behaviors remain constant. Research 2 Experimental Research: Quasi-Experimental Research Designs 3. Single-Subject Experimental Designs b. Single-Subject Multiple-Baseline Design Once the first behavioral shift is identified, the intervention is applied to the next behavior, and so on. The logic behind this design is that it would be highly unlikely for baseline behaviors to successively shift by chance. Research 2 Experimental Research True Experimental Research 1. Randomized True Group Design *Randomized Two-Group Posttest Only Design *Randomized Two-Group Pretest-Posttest Design 2. Solomon Four-Group Design 3. Factorial Design Research 2 Experimental Research Quasi-Experimental Research 1. Nonequivalent Comparison-Group Design -Nonequivalent Groups Posttest-Only (Two or More Groups) -Nonequivalent Groups Pretest-Posttest (Two or More Groups 2. Interrupted-Time Series Design -Simple Interrupted Time-Series Design -Reversal Time-Series Design -Multiple Time-Series Design 3. Single-Subject Experimental Designs -Single-Subject Reversal Design -Single-Subject Multiple-Baseline Design Pre-experimental Research Research 2 Pre-experimental Research Pre-experimental research design is a research scheme in which a subject or a group is observed after a treatment has been applied. It is used to test whether the treatment has the potential to cause change. Research 2 Pre-experimental Research Pre-experimental designs are the simplest of the group research designs and involve the assessment of the functioning of a single group of persons who receive social work services. Research 2 Experimental Research: Pre-Experimental Research Designs 1. One-Shot Case Study Design A single group is studied at a single point in time after some treatment that is presumed to have caused change. Research 2 Experimental Research: Pre-Experimental Research Designs 1. One-Shot Case Study Design The carefully studied single instance is compared to general expectations of what the case would have looked like had the treatment not occurred and to other events casually observed. No control or comparison group is employed. Research 2 Experimental Research: Pre-Experimental Research Designs 2. One-Group Pretest-Posttest Design A single case is observed at two time points, one before the treatment and one after the treatment. Changes in the outcome of interest are presumed to be the result of the intervention or treatment. No control or comparison group is employed. Research 2 Experimental Research: Pre-Experimental Research Designs 3. Static Group Comparison A group that has experienced some treatment is compared with one that has not. Observed differences between the two groups are assumed to be a result of the treatment. Research 2 Experimental Research True Experimental Research 1. Randomized True Group Design *Randomized Two-Group Posttest Only Design *Randomized Two-Group Pretest-Posttest Design 2. Solomon Four-Group Design 3. Factorial Design Research 2 Experimental Research Quasi-Experimental Research 1. Nonequivalent Comparison-Group Design -Nonequivalent Groups Posttest-Only (Two or More Groups) -Nonequivalent Groups Pretest-Posttest (Two or More Groups 2. Interrupted-Time Series Design -Simple Interrupted Time-Series Design -Reversal Time-Series Design -Multiple Time-Series Design 3. Single-Subject Experimental Designs -Single-Subject Reversal Design -Single-Subject Multiple-Baseline Design Research 2 Experimental Research Pre-experimental Research 1. One-shot Case Study 2. One group Pretest and Posttest Design 3. Static Group Comparison Types Non- Experimental Research Research 2 Non-Experimental Research 1. Survey Research Survey research means collecting information about a group of people by asking them questions and analyzing the results. Research 2 Non-Experimental Research 1. Survey Research Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people. Research 2 Non-Experimental Research 1. Survey Research To conduct an effective survey, follow these six steps: 1. Determine who will participate in the survey 2. Decide the type of survey (mail, online, or in-person) 3. Design the survey questions and layout 4. Distribute the survey 5. Analyze the responses 6. Write up the results Research 2 Non-Experimental Research 2. Descriptive- Normative Survey A descriptive-normative survey combines two research methods: gathering information to describe the object of study as it is, has been or is viewed (descriptive method); and critiquing of the object to identify ways to improve it (normative method). Research 2 Non-Experimental Research 2. Descriptive- Normative Survey This is an extension of the descriptive survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm. Research 2 Non-Experimental Research 2. Descriptive- Normative Survey For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role. Research 2 Non-Experimental Research 2. Descriptive- Normative Survey If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory. Research 2 Non-Experimental Research 3. Descriptive- Status This is a quantitative description technique that seeks to answer questions about real- life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance. Research 2 Non-Experimental Research 3. Descriptive- Status A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa. Research 2 Non-Experimental Research 4. Comparative In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. Research 2 Non-Experimental Research 4. Comparative For example, an examination body wants to determine the better method of conducting tests between paper-based and computer- based tests. Research 2 Non-Experimental Research 4. Comparative A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method. Research 2 Non-Experimental Research 5. Evaluative This research is a type of research used to evaluate a product or concept, and collect data to help improve your solution. Evaluative research has many benefits, including identifying whether a product works as intended, and uncovering areas for improvement within your solution. Research 2 Non-Experimental Research 5. Evaluative It is as also known as evaluation research or program evaluation. Evaluation research is typically introduced in the early phases of the design process to test existing or new solutions and continue to be employed in an iterative way until the product becomes ‘final’. Research 2 Non-Experimental Research 6. Correlational Correlational research is a type of research design commonly used in the social and behavioral sciences. It measures the relationship between two or more variables. Research 2 Non-Experimental Research 6. Correlational Researchers using correlational research design typically look at associations or correlations in data without establishing that one event causes another. To statistically analyze correlational data, researchers must control variables that may affect the relationships found in the data. Research 2 Non-Experimental Research 7. Causal-Comparative Causal-comparative research is a methodology used to identify cause-effect relationships between independent and dependent variables. Researchers can study cause and effect in retrospect. This can help determine the consequences or causes of differences already existing among or between different groups of people. Research 2 Non-Experimental Research 7. Causal-Comparative When you think of Casual Comparative Research, it will almost always consist of the following: A method or set of methods to identify cause/effect relationships A set of individuals (or entities) that are NOT selected randomly – they were intended to participate in this specific study Research 2 Non-Experimental Research 7. Causal-Comparative When you think of Casual Comparative Research, it will almost always consist of the following: Variables are represented in two or more groups (cannot be less than two, otherwise there is no differentiation between them) Non-manipulated independent variables – *typically, it’s a suggested relationship (since we can’t control the independent variable completely) Multivariate Analysis  Research 2 Multivariate Analysis In data analytics, we look at different variables (or factors) and how they might impact certain situations or outcomes. For example, in marketing, you might look at how the variable “money spent on advertising” impacts the variable “number of sales.”  Research 2 Multivariate Analysis In the healthcare sector, you might want to explore whether there’s a correlation between “weekly hours of exercise” and “cholesterol level.” This helps us to understand why certain outcomes occur, which in turn allows us to make informed predictions and decisions for the future.  Research 2 Multivariate Analysis There are three categories of analysis to be aware of: Univariate analysis, which looks at just one variable Bivariate analysis, which analyzes two variables Multivariate analysis, which looks at more than two variables Research 2 Multivariate Analysis 1. Regression Analysis Multiple linear regression is a dependence method which looks at the relationship between one dependent variable and two or more independent variables. Research 2 Multivariate Analysis 1. Regression Analysis A multiple regression model will tell you the extent to which each independent variable has a linear relationship with the dependent variable. This is useful as it helps you to understand which factors are likely to influence a certain outcome, allowing you to estimate future outcomes. Research 2 Multivariate Analysis 2. Analysis of Variance (ANOVA) ANOVA, which stands for Analysis of Variance, is a statistical test used to analyze the difference between the means of more than two groups. A one-way ANOVA uses one independent variable, while a two-way ANOVA uses two independent variables. Research 2 Multivariate Analysis 2. Analysis of Variance (ANOVA) One-way ANOVA example As a crop researcher, you want to test the effect of three different fertilizer mixtures on crop yield. You can use a one-way ANOVA to find out if there is a difference in crop yields between the three groups. Research 2 Multivariate Analysis 2. Analysis of Variance (ANOVA) Use a one-way ANOVA when you have collected data about one categorical independent variable and one quantitative dependent variable. The independent variable should have at least three levels (i.e. at least three different groups or categories). Research 2 Multivariate Analysis 3. Interdependent Analysis Used to determine the relationship between a set of variables among themselves. Research 2 Multivariate Analysis 4. Discriminant Analysis Discriminant Analysis refers to a statistical technique that may determine group membership based on a collection of metric predictors that are independent variables. The primary function of this technique is to assign each observation to a particular group or category according to the data’s independent characteristics. Research 2 Multivariate Analysis 4. Discriminant Analysis Discriminant Analysis refers to a statistical technique that may determine group membership based on a collection of metric predictors that are independent variables. The primary function of this technique is to assign each observation to a particular group or category according to the data’s independent characteristics. Research 2 Multivariate Analysis 5. Multiple logistic regressions Multiple logistic regressions, meanwhile, examine the probability of one of two events occurring. Will one’s partner accept an offer of marriage? Will a child graduate from college? In both scenarios, myriad factors may contribute to the final outcome — has the partner expressed interest in marriage previously? Research 2 Multivariate Analysis 5. Multiple logistic regressions Does the child study hard? Ultimately, both come down to a simple yes or no. For a business owner trying to determine how likely a certain kind of client is to contract with her demolition company for a job, multiple logistic regression is the way to go. Research 2 Multivariate Analysis 6. Multivariate analysis of variance (MANOVA) Multivariate analysis of variance (MANOVA) tests the difference in the effect of multiple independent variables on multiple dependent variables. Say, for example, a marketer wants to study the impact of pairing a price reduction with an increase in campaign budget — both independent variables — on the sales of a certain face cream. Research 2 Multivariate Analysis 6. Multivariate analysis of variance (MANOVA) Moving inventory isn’t her only concern, however. She also wants to know what the new price and spend will do to her total revenues on the cream for that period. Both sales and revenues represent dependent variables. In this case, a MANOVA would prove most helpful. Research 2 Multivariate Analysis 7. Factor analysis Sometimes too many variables find their way into a dataset. When that happens, it can be difficult to identify any clear patterns in all the information spread out in front of you. Trim back some of those variables using factor analysis, and you can begin to make sense of your data. Research 2 Multivariate Analysis 7. Factor analysis Do this by combining closely correlated variables, such as condensing a target audience’s income and education into “socioeconomic status” — or multiple behaviors, such as leaving a positive review and signing up for your newsletter into “customer loyalty.” Research 2 Multivariate Analysis 8. Cluster analysis Like factor analysis, cluster analysis is a technique you can use to turn down the noise in your data to zero in on what’s most important. Only instead of grouping similar factors together, cluster analysis includes combining similar observations. A scientist performs cluster analysis when, upon discovering new types of deep-sea fish, she organizes them into a single species based on shared traits. Research 2 Multivariate Analysis 8. Cluster analysis Applied to marketing, cluster analysis represents a powerful market segmentation tool that — when done regularly using powerful, automated software — can help teams deliver personalized experiences based on similar relevant behaviors. Research 2 Multivariate Analysis 9. Conjoint Analysis Conjoint analysis refers to the process of surveying consumers to identify which part of a product or service they value most. Used widely in market research, conjoint analysis provides real-world insight into which factors consumers consider most important when making a purchase. Research 2 Multivariate Analysis 9. Conjoint Analysis Such data is invaluable for minimizing guesswork when it comes to rolling out new products or services (or when tweaking old ones). Not all feedback deserves equal weight, however. Only invest in a survey that is sure to reach consumers that match your target audience for the product. Research 2 Multivariate Analysis 9. Conjoint Analysis Just asking the right people isn’t enough. For a response of any real value, you’ll want to be sure to survey as many individuals as possible so as to root out outlying opinions and establish a statistically significant trend. Activity 3 Matching the Different Situations to Presented Research Designs Research 2 Activity 3 1 2023 Barangay and SK Pre-Election Survey Research 2 Activity 3 1 2023 Barangay and SK Pre-Election Survey Survey Research 2 Activity 3 2 Cocos nucifera L. oil (niyog) as an effective medicinal plant for SARS-CoV-2 Activities Research 2 Activity 3 2 Cocos nucifera L. oil (niyog) as an effective medicinal plant for SARS- CoV-2 Activities Experimental Research 2 Activity 3 3 Association of Social Media Involvement to Mental Health at School of Students Research 2 Activity 3 3 Association of Social Media Involvement to Mental Health at School of Students Correlation Wrapping- Up Research 2 Wrapping-Up 1 What are the major types of quantitative research? Research 2 Wrapping-Up 2 Give one example of quantitative research design and discuss. Assignment Research 2 Assignment None  Thank you! 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