Statistics in Psychological Research: Variables, Hypotheses, and Data Analysis, Apuntes de Estadística

¡Descarga Statistics in Psychological Research: Variables, Hypotheses, and Data Analysis y más Apuntes en PDF de Estadística solo en Docsity! Topic 1: The process of scientific research 1. Research, knowledge generation, science in psychology. 2. Role of Statistics in Psychology. 3. Basic statistical concepts (sample, population, sampling, etc). 4. Theories, Models, Questions / problems, hypotheses. 5. Variables: Definition, types and scales of measurement. 6. Research methods and design 7. Data analysis, interpretation and evaluation of results. 8. The research report. BLOCK I: Introduction Spanish Análisis de datos en Psicología I., Botella et al. Pirámide English Bock, Velleman y de Veaux (2010, 3rd ed.). Stats: Modeling the World. Pearson Education. Openintro book (Statistics): https:// www.openintro.org/stat/textbook.php?stat_book= os Methods. Price: Psychology Research Methods: Core Skills and Concepts v. 1.0 http://2012books.lardbucket.org/books/psychol ogy-research-methods-core-skills-and-concepts/ Bibliography • Objectives: Scientific knowledge aims to be established in the form of laws more generally possible. • How this knowledge is acquired: Scientific knowledge is acquired using a standardized method: the scientific method. One main feature is replicability, allowing consensus within the scientific community. 1. Research, knowledge generation, science in psychology. • Method of science: hypothetical-deductive method. • Hypothesis: A hypothesis is a predictive announced on the expected outcome of the investigation. Its requires verification and leads to a conclusion • Theory: Set of related hypotheses that provide a plausible explanation for a phenomenon or group of phenomena. • Inductive method: Reasoning from the particular to the general • Deductive method: Reasoning from the general to the particular 1. Research, knowledge generation, science in psychology. Research methods in psychology (I) Steps to examine a research problem: Definition of the problem Deduction of testable hypotheses Establishing a data collection procedure Analysis of the results Discussion of these results Writing a research report 1. Research, knowledge generation, science in psychology. 1.2. Función de la Estadística en Psicología. Empirical psychological research Data collection Data analysis (Statistics) Phase 1: Exploratory/descriptive analyses (Descriptive statistics) Fase 2: Hypothesis testing (Inferential statistics) Conclusions and generation of new hypotheses Role of Statistics in Psychology. Mozart Effect Hypothesis (scientific): Subjects who listen to Mozart music improve performance on intelligence tests more than those who do not listen to Mozart. Experiment. Half of the participants (randomly selected) is presented with music of Mozart, the other half are presented chillout music. Then, we conduct an intelligence test. According to the above hypothesis, one would expected differences in intelligence between the two groups. Statistical hypothesis. The null hypothesis (H0) indicates no effect and the "alternative hypothesis" (H1) indicates presence of an effect. The means and standard deviations of the group "Mozart" and the group "chillout" are calculated and the corresponding inference test is performed. We obtained a “p” value: this indicates how likely is to get the obtained result (or a more extreme result) assuming that the null hypothesis is true. (Notice that the researcher typically want to reject the null hypothesis.) 1.2. Función de la Estadística en Psicología. . i l t í ti i l í .Role of Statistics in Psychology. Independent variable (the variable that has been manipulated/selected): Type of music (Mozart vs. chillout) Dependent variable (the variable that is being measured;): CI after listening to music N = 10 (Randomization to groups; 5 subjects each group) 1.2. Función de la Estadística en Psicología Example : . . i l t í ti i l í .Role of Statistics in Psychology. Basic statistical concepts • Population: The set of all elements that share one or more characteristics. • We can have a finite population (e.g., psychology students in Spain) or an infinite population (e.g., the set of even numbers). • (Normally, we will work with samples.) • Sample: Subset of elements of a population. • Objective: To be able to describe the population. • To do this, the sample must be representative of its respective population. Basic statistical concepts • Parameter: A descriptive property of the population. They are symbolized with Greek letters (m for the mean, s for standard deviation). • Statististic: A descriptive property of the sample. They are symbolized with Latin letters (X for the mean, s for standard deviation). Basic statistical concepts Univariant and Multivariant analyses • Univariate analysis: We organize and summarize data, treating each variable in isolation. • Multivariate analysis: In this case, we examine the relationship between two or more variables simultaneously. Basic statistical concepts Theme 1: The process of scientific research 1. Research, knowledge generation, science in psychology. 2. Role of Statistics in Psychology. 3. Basic statistical concepts (sample, population, sampling, etc). 4. Theories, Models, Questions / problems, hypotheses. 5. Variables: Definition, types and scales of measurement. 6. Research methods and designs. 7. Data analysis, interpretation and evaluation of results. 8. The research report. Theories, Models, Questions / problems, hypotheses. Scienfical theories (taken from Wikipedia): In science, the term "theory" refers to "a well-substantiated explanation of some aspect of the natural world, based on a body of facts that have been repeatedly confirmed through observation and experiment.” Theories must also meet further requirements, such as the ability to make falsifiable predictions with consistent accuracy across a broad area of scientific inquiry, and production of strong evidence in favor of the theory from multiple independent sources. The strength of a scientific theory is related to the diversity of phenomena it can explain, which is measured by its ability to make falsifiable predictions with respect to those phenomena. Theories are improved (or replaced by better theories) as more evidence is gathered, so that accuracy in prediction improves over time; this increased accuracy corresponds to an increase in scientific knowledge. Scientists use theories as a foundation to gain further scientific knowledge, as well as to accomplish goals such as inventing technology or curing disease. Example: theory of relativity Appendix U Code in R for the Overlap Model This code will print out overlap values and response prob. Ascsuming that one of the target is the string "12345" for replacements, use “6” Example 1: replacement of second letter i É $ Edit to modify the other alternative + + d foil=0(1,6,3,4,5) di Example 2: transposition of letters 2 and 3 foil = c(1,3,2,4,5) $ Edit to change parameter values sl to sí and a par=c(.404,1.094,1.179,1.659,1.743,3.941) atrix (0,5,5) for[j in 1:5)1 for(i in 1:5)[ ov[i,j]=pnorm(bo[i+1] mn [3] .s4[31) —pnorm(bo([i] .mn[j].sa[31) ) ) ov=rbind(ov.c(0.0,0,0,0)) x=0 y=0 m<-c(1,2,3,4,5) forli in 1:5)x=x+esum(ov[foi1[3],1]) for(i in 1:5)y=y+sum(ov[m[i].i]) p=x"al/(x"al+y”al) print(“overlap value”); print(x) print("response p."); print(1—p) Reccived May 15, 2006 Revision received May 6, 2008 Accepted May 7. 2008  Table 2 Results From Experiments la and Ib Transpositions Replacements Conditions M (2 SES) Model M (2 SEs) Model Experiment la Land 2 906 (.029) 889 923 (037) 37m 2 and 3 625 (042) St 826(.058) 848 3 and 4 576 (041) 570 768 (049) 197 4and5 806 (.025) 531 749 (.060) 147 land 3 922 (033) 953 935 (028) 967 2 and 4 704.051) m3 .783 (050) 808 3 and 5 675.045) 688 197 (045) 10 land 4 912 (.027) 941 936 (004) 951 2and5 725.043) 1 799 (045) 803 1 927 (028) 887 2 117 (052) 589 3 133 (051) 576 4 663 (.050) 526 5 657 (039) 520 Experiment 1b Land 2 865 (.041) 870 2 and 3 626.062) 808 840.052) 887 3 and 4 806 (.049) 504 808 (065) 870 4and5 .658 (.042) 558 807 (052) 830 2 and 4 686 (064) 705 807 (060) 843 3 and 5 749 (.060) 166 852 (040) 876 2and5 175.054) 808 854(.04) 850 2 798 (054) 597 3 8156042) 734 4 720 (048) 570 5 20 (057) 579 Problem: Question to resolve arising from daily life, practical needs, contradictory results, etc. A sentence, sometimes interrogative, indicating a relationship between variables. One must have creativity and originality, and the question should be interesting and well-constructed Example: The behavioral aspects associated with stuttering (stuttering) are influenced by excessive muscle tension? Theories, Models, Questions / problems, hypotheses. • Measurement is the process of attributing numbers to characteristics. • Assigning numbers to characteristics is done by following rules (Stevens, 1949). . Variables: Definition, types and scales of measurement. SCALES in PSYCHOLOGY • 1) Nominal Scale: The assigned numbers only serve to distinguish categories. Sex (0 = male, 1 = female). Relationship: same-different • 2) Ordinal scale: The numbers indicate not only equality / inequality (nominal scale) but also a relationship of order. Depression level (0 = low, 1 = medium, 2 = high). Relationship: same-different and order . Variables: Definition, types and scales of measurement. SCALES IN PSYCHOLOGY • 3) Interval scales: In this case we already have measurement unit (that is, we know the difference between elements). The origin of the scale is arbitrary. Temperature in degrees Celsius or Fahrenheit. Relationship: same-different order, constant unit • 4) Ratio scales. In this case, we have both measurement unit as an absolute 0. In this case, we have relations of equality / inequality of reasons. Weight, height. Relationship: same-different, order, constant unit, absolute zero. . Variables: Definition, types and scales of measurement. • Manipulative-experimental tradition: • nomothetic approach: Search of general laws of behavior. • The independent variable/s are manipulated to see their/its impact on the dependent variable/s. • Determination of causal relationships. • Laboratory research controlling for confounding variables. Research methods and design  Correlational-associative tradition  Idiographic approach: Evaluation of differences between individuals or groups.  Determination of correlations/associations between variables or factors.  Field research.  Main types of non-experimental research:  Survey methodology.  observational methodology (case studies).  Qualitative Methodology (e.g., interviews). Research methods and design – Survey methodology: – Its aim is to describe characteristics of a population fromresponses to surveys or questionnaires. – Observational methodology: – Its aim is to describe phenomena occurring in natural environments. It is a systematic record of behavior. – Qualitative Methodology: – Its aim is to describe a phenomenon seeking more meaning than quantification. Research methods and design