NCMB-311: Nursing Research 1 - Week 7 - Data Collection

NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 7 – Data Collection in Quantitative and Dichotomous Question Qualitative Research Ex:...

NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 7 – Data Collection in Quantitative and Dichotomous Question Qualitative Research Ex: 1. Have you ever been pregnant? Data Collection in Quantitative Research o Yes 1. Self-Report Data (Patient-reported o No outcomes) Multiple Choice Question Ex: Types of instrument: Interview schedule and 1. How important is it to you to avoid a Questionnaire (self-administered questionnaire) pregnancy at this time? Interview schedule advantage: o Extremely important o Very important Response rates – tends to be higher in o Somewhat important a face to face interview because people o Not important are more likely to talk to an interviewer Forced Choice Question than answer an e-mailed questionnaire. Ex: Audience – quality of audience because 1. Which statement most closely not all people cannot fill out represents your point of view? questionnaires such as people who are o What happens to me is my own doing. blind, young children, elderly or o Sometimes I feel I don’t have enough uneducated. control over my life. Questionnaire advantages: Rating Question Ex: Cost – much less costly or less - On a scale from 0 to 10, where 0 inexpensive than interviews. means “extremely dissatisfied” and 10 Anonymity – it offers possibility of means “extremely satisfied”, how complete anonymity. Respondents are satisfied were you with the nursing not required to disclose their names. It care you received during your also often results into a higher proportion hospitalization? of responses, revealing socially o Scale from 0 (extremely dissatisfied) to undesirable viewpoints than interviews. 10 (extremely satisfied) Close and Open-ended Questions Open-ended: It Example: Summated Rating Scales allows people to “What was your - Scale provides numeric scores to place respond in their own biggest challenge respondents on a continuum with respect words. after your surgery?” to an attribute. Close-ended (fixed- Example: Likert Scale alternative): It Dichotomous - It is a widely used scaling technique. provides the Multiple choice - It consists of several declarative items that express respondents’ viewpoints on respondents options, Forced choice a topic. that may choose. Rating - After the respondents completed the scale, their response will be recorded. 1989 (T.V.) 1 | JK  Response Set Bias Checklist Social Desirability Response Set Bias - Category systems are used to construct - Tendency of some individuals to a checklist. misrepresent themselves by giving - The instrument observers use to record answer that are congruent with prevailing observed phenomena. social views. May tally occurrence of behaviors - This can be minimized, by creating a non- Non-exhaustive system – record judgmental atmosphere, providing occurrence in checklist. anonymity and encouraging frankness. Rating Scale Extremely Response Set Bias - Alternative to checklist. - A bias reflecting consistent selection of extreme alternatives. Observation Sampling - Respondents who always choose - Researchers must decide when and for strongly agree and strongly disagree, how long the structured of observation despite having other options. instruments will be used. Acquiescence Response Set Bias - Observations are usually done within a specific amount of time, and the amount - Respondents who agree with statements of time is a standardized. regardless of content. (yeah-sayers) - It is focused on selecting behaviors and - Respondents who disagree with activities to be observed, not the statements regardless of content. (nay- selection of participants. sayers) Time Sampling 2. Structured Observational Methods - Researchers select time periods during Structured Observation which observations will occur. - Used to record behaviors, actions and Event Sampling events. - Using formal instruments and protocols - Uses integral behavior sets or events for that specify what to observe, how long to observation. observe it, and how to record information. Potential Biases in Observational Methods Methods of Recording Structured Participants Observation - Wanted to “look good”, awareness of - A category system is an attempt to assign being observed or shyness in front of in a systematic fashion the qualitative strangers or a camera. behaviors and events. Exhaustive (Ex. body positions) Observer, Human Perceptual Errors Non-exhaustive (Ex. children - Observation and interpretations are with aggressive behavior → demanding biases. strikes another child or kicks/hits a - To make and record observation in a wall) completely objective passion is challenging and perhaps impossible. 1989 (T.V.) 2 | JK 3. Biomarkers - It is important not to take sides on any controversial issue and not to appear too - Also called biophysiological measures. strongly affiliated with a particular - Purposes of using biomarkers in subgroup of the culture. nursing research: Studies about basic Pace of Data Collection biophysiologic processes. - Is often an intense and exhausting Explorations of the ways in which experience, especially if the phenomena nursing actions and interventions studied concerns with illness or other life affects physiologic outcomes. stressful events. Studies to evaluate the accuracy Collect data at a pace that of biophysiologic information minimize stress. gathered by nurses. Limit interviewing to no more than Studies of the correlates of one a day and to engage in physiologic functioning in patients emotionally releasing activities. with health problems. - Debrief about any feelings of distress Types of Biophysiologic Measures with co-researcher, colleague or advisor. In Vivo Measurements Emotional Involvement with Participants - Performed directly in or on living - Need to guard against a pitfall that has organisms. (Ex. Measuring blood been called “going native”. pressure) - Compromising their ability to collect meaningful and trustworthy data. In Vitro Measurements Becoming overwhelmed with - Performed outside the organism’s body. participants’ suffering. (Ex. Laboratory analysis of blood or urine - Be supportive and to listen carefully to samples) people’s concerns. Not advisable to intervene and try Data Collection in Qualitative Research to solve their problems or to share Field Issues in Qualitative Research personal problems with them. Gaining Trust Reflexivity - Researchers need to develop strategies - Refers to researchers’ awareness of in the field to establish credibility among themselves as part of the data they are those being studied. collecting. - Must try to “be like” the people being What is the part they play in their studied while at the same time keeping a own study? certain distance. How can one’s behavior affect - “Being like” participants mean that data obtained? researchers should be sensitive to such Unstructured Interviews issues as styles of dress, modes of speech, customs and schedules to be - Conversational and interactive and are able to get together with participants and the mode of choice when researchers do gain their trust. not have a clear idea of what it is they do not know. 1989 (T.V.) 3 | JK  - Researchers using unstructured Can be unstructured or semi- interviews do not have a set of prepared structured. questions. Challenging for people with Often begin by informally asking a inadequate literacy skills. broad question. Sometimes called Required high level participation a grand tour question relation to of study participants. the research topic. Gathering Qualitative Self-Report Data Semi-Structured Interviews (Focused) - Wording of questions should reflect the - Prepare a written topic guide, which is a worldviews and language of participants. list of areas or questions to be covered - Being a good listener is equally important with each participant. as being able to ask good questions. Questions should be ordered in a - Recording interviews logical sequence, perhaps ✓ Interview notes during interview chronologically or perhaps from ✓ Audio recording → verbatim the general to the specific. transcription Topic guide might include Qualitative Observational Methods suggestions for probes. Questions should give people an Participant Observation opportunity to provide rich detailed - Participate in the functioning of the social information. group under investigation. Focus Group Interviews - Characterized by prolonged periods of social interaction between researchers - Group of people (usually five or more) is and participants, in the participant’s assembled for a discussion. sociopolitical and cultural milieu. People selected are fairly homogeneous group to promote a Observer-Participant Role in Participant comfortable group dynamic. Observation Researchers as the moderators. - According to Junker (1960): Photo Elicitation Complete participants conceal their identity as researchers, - Involves an interview stimulated and entering the group ostensibly as guided by photographic images. regular members. Photovoice Compete observers do not attempt participation in the group’s - Participants take photographs activities but rather make themselves and then interpret them. observations as outsiders. Diaries Observers must overcome at least two initial - For historical and non-historical hurdles: research. - Gaining entrée into the social group – Can be useful in providing an otherwise, will be restricted to “front intimate and detailed description stage” knowledge. (Leininger, 1986) of a person’s everyday life. 1989 (T.V.) 4 | JK  - Establishing rapport and developing trust “When the sun came up, I was looking at within the social group – to get to the you” “back stage” - Out of the Woods Gathering Unstructured Observational Data Physical Setting – What are key features of the setting? Participants – What are the characteristics of the people being observed? Activities – What is going on? Frequency and Duration – When did the activity or event begin, and when is it scheduled to end? Process – How is the event or interaction organized? Outcomes – Why is the event or interaction happening? Sampling Observations and Selecting Observational Location Single positioning means staying in a single location. Multiple positioning involves moving around the site to observe behaviors from different locations. Mobile positioning involves following a person throughout a given activity or period. Recording Observations - Log (Field diaries) – daily record of events and conversations in the field. - Field Notes – represents the participant observers’ efforts to record information and also to synthesize and understand the data. Descriptive notes (observational notes) are objective descriptions of observed events and conversations. Reflective notes, which document the researcher’s personal experiences, reflections, and progress while in the field. 1989 (T.V.) 5 | JK  NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 8 – Sampling Techniques Sampling Frame – a list of population elements) Sampling in Quantitative Research ✓ Stratified Random Sampling – - Knowledge about the world is partial and involves taking certain areas of temporary in terms of research. the population, dividing the areas ✓ Our knowledge approximates the into sections and then taking a world but not an actual random sample from each representation of the world. section. - Sample → Population ✓ Systematic Random Sampling – ✓ Population is the entire group of involves selecting every kth case interest. from a list, such as every 10th (Ex. people using social media) person on a patient list or every ✓ Sample is a subset of population 25th person on a student roster. elements; cases/elements that ✓ (Multistage) Cluster Random represent the population. Sampling – involves selecting broad groups (clusters) rather Population, Sampling and Strata than selecting individuals. - Researchers specify population Non-Probability Sampling – elements characteristics through eligibility criteria. are selected by non-random methods. ✓ Inclusion Criteria – to determine ✓ Accidental, Convenience, whether a person qualifies as a Incidental – utilizes readily member of a population. available subjects. ✓ Exclusion Criteria – it excludes ✓ Quota Sampling – identify strata someone as a member of a of the population and then population. determine how many participants - Representativeness of the sample. are needed from each stratum to ✓ Sampling Bias – failure to reach meet a quota. representativeness ✓ Consecutive Sampling – - Strata – segment of a population based involves recruiting all people from on shared characteristics. an accessible population over a ✓ Use of strata may help enhance specific time interval or for a sample’s representativeness. specified sample size. ✓ Purposive or Judgmental – Categories of Sampling Plan subjects are hand-picked to be Probability Sampling – a process in included in the sample based on which each element of the population has the researcher’s knowledge of the an equal chance of being chose for the population. sample. There is random selection. Evaluating (Non-) Probability Sampling ✓ Simple Random Sampling – sampling by chance, either by - Probability sampling is the best method lottery or by the use of a table of of obtaining representative samples. random numbers. (Uses 1989 (T.V.) 6 | JK  - Probability sampling allows researcher to - Do not articulate an explicit population to estimate the magnitude of sampling whom results are intended to be error. (Sample values vs. population generalized, but they establish the kinds values) of people who are eligible to participate in - The drawback of probability sampling is their research. its impracticality. - Practical issues also affect who can be included in the sample. Sample Size in Quantitative Studies Types of Qualitative Sampling - Quantitative researchers need to pay attention to the sample size needed to Convenience Sampling – utilizes readily achieve statistical conclusion validity. available informants. ✓ Should use as large a sample as ✓ Sampling is not a preferred sampling possible – the larger the sample, approach, even in qualitative studies. the smaller the sampling error. - When non-probability sampling is used, Snowball Sampling – asking early informants even large sample can harbor bias. to refer other study participants. - Power Analysis – to estimate sample ✓ More cost-efficient and practical size. ✓ Easier time establishing a trusting - G*Power – free software for power relationship with new participants. analysis. ✓ Can readily specify the characteristics of Sampling in Qualitative Research target new participants. Logic of Qualitative Sampling Purposive Sampling – utilizes readily available informants. - Qualitative – to discover meaning and to uncover multiple realities, not to ✓ Maximum Variation Sampling – generalize to a target population. involves purposefully selecting persons ✓ Who would be an information-rich or settings with variations on dimensions data sources for my study? of interest. ✓ Who should I talk or observe to ✓ Typical Case Sampling – involves maximize my understanding of the selecting cases that illustrate or highlight phenomenon? what is typical, average, normal or - A key step in Qualitative sampling is to representative. select settings with high potential for ✓ Extreme (Deviant) Case Sampling – information richness. provides opportunities for learning from - Additional sampling questions as studies the most unusual and extreme progress. informants. ✓ Who can confirm my ✓ Criterion Sampling – involves selecting understanding? cases that meet a predetermined ✓ Challenge or modify my criterion of importance. understanding? ✓ Sampling confirming and ✓ Enrich my understanding? disconfirming cases. - Sampling is emergent and capitalizes on Theoretical Sampling – is used in grounded early learning to guide subsequent theory. actions. 1989 (T.V.) 7 | JK  ✓ “What types of people should the researchers turn to next to further the theoretical development of the emerging conceptualization?” Sampling in Ethnography May begin by adopting a “big net” approach. Often rely on a small pool of key informants. May also sample non-human – event, records or artifacts. Sampling in Phenomenology Often rely on a small pool key informant (can be 1- or fewer). May also recruit people with demographic or other differences who have shared a common experience – to explore diversity of individuals experiences. Sampling in Grounded Theory Uses theoretical sampling. Select informants who can best contribute to the evolving theory. Appraising Qualitative Sampling Plans - Adequacy refers to the sufficiency and quality of data the sample yielded. - Appropriateness concerns the methods used to select a sample. ✓ Results to identification and use of participants who can best provide information according to the conceptual requirements of the study. “You got that red lip classic thing that I like” - Style 1989 (T.V.) 8 | JK  NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 9 – Assessing Quality and Statistics: Trustworthiness of Research - ICC if the measurements yield Measurement of Quality in Quantitative continuous data. Research - Cohen’s Kappa when rating are categorical data - We need to ensure the quality of our < 0 = no agreement research instrument. < 0.01 – 0.20 = none to slight agreement Taxonomy of Measurement Properties < 0.21 – 0.40 = fair agreement < 0.41 – 0.60 = moderate agreement 1. Reliability < 0.61 – 0.80 = substantial agreement - Is the extent to which scores are free < 0.81 – 1.00 = almost perfect agreement from measurement error. The extent to which scores for Parallel Test Reliability people who have not changed are - Not common in health research but there the same for repeated are instances where there are different measurements. versions of research instruments. Absence of variations. - Measurement of the same attribute using 1.1 Reliability - Different approaches alternate versions of the same instrument, with the same people Test-Retest Reliability (repetition over versions). - Administration of the same measure to Reliability coefficient (R) the same people on two occasions (repetition over occasions) 0.00 – no reliability - Interclass correlation coefficient – 1.00 – perfect reliability obtains at least 30 heterogeneous Factors Affecting Reliability samples: < 0.50 = poor reliability - Those that can be controlled by the 0.50 – 0.75 = moderate reliability researchers. 0.75 – 0.90 = good reliability Ex. In observational methods – > 0.90 = excellent reliability precision in defining categories or greater clarity in explaining the Interrater Reliability underlying construct, through - Measurements by two or more observers observer training. or raters using the same instrument - Heterogeneity – homogenous sample = (repetition over persons). lower reliability coefficient. - Reliability is not a fixed property of an Intrarater Reliability instrument. - Measurement by the same observer or 2. Internal Consistency rater on two or more occasions (repetition over occasions). - Consistency of scores across items in the research instrument. 1989 (T.V.) 9 | JK  A research instrument is said to be Trustworthiness and Integrity in Qualitative internally consistent if the items Research can be used to measure the same Lincoln and Guba’s Quality Criteria (1985 - trait or attribute. 1994): Coefficient alpha or Cronbach’s alpha for evaluating internal Credibility Refers to confidence in the truth of consistency. the data and interpretations of them. 0.9 or higher = excellent IC - Carrying out the study in a way that 0.8 – 0.9 = adequate IC enhances the believability of the findings. 0.7 – 0.8 = marginal IC - Taking steps to demonstrate credibility in 0.6 – 0.7 = poor IC research reports. Less than 0.6 = unacceptable IC - Ex. Saturation, Triangulation Validity Dependability - Degree to which an instrument is - Refers to the stability or reliability of data measuring the construct it purposes to over time and conditions. measure. - Ex. Triangulation - Difficult to gauge Confirmability Face Validity – whether the instrument looks like it is - Refers to the potential for congruence measuring the target construct. between two or more independent Content Validity – may be people about the data’s accuracy, defined as the extent to which an relevance or meaning. instrument’s content adequately - Ex. Triangulation captures the construct. Transferability Criterion Validity – is the extent to which the scores on an - Refers to the extent to which finding can instrument are a good reflection of be transferred to or have applicability in a “gold standard” that is a criterion other setting or groups. considered an ideal measure of - Ex. Saturation the construct. Not all measures Authenticity can be validated using criterion approach. - Refers to the extent to which researchers Construct Validity – is the to fairly and faithfully show a range of which evidence about degree realities. measure scores in relation to - Emerges when it conveys the feeling other scores supports the tone of participants’ lives as they are inference that the construct has lived. been appropriately represented. - Ex. Thick and vivid description Not all measures can be validated “I want you for worse or for better” using criterion approach. - How you get the Girl 1989 (T.V.) 10 | JK  NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 10 – Attending to Ethics in Research 2. Human Dignity – Right to self-determination Ethical Dilemmas in Conducting Research Self-determination means that prospective participants can voluntarily Ethical dilemmas may happen when: decide whether to take part in a study, The rights of the study participants without risk of prejudicial treatment. and the quality of the study are put ✓ Also means that people have the in direct conflict. right to ask questions, to refuse, to Nurses face conflict of interest give information and to withdraw situations. from the study. Nurse researchers’ behaviors A person’s right to self-determination conflicts with the expected includes freedom from coercion. standard behavior of a researcher. ✓ Threats of penalty from failing to Ethical Principles for Protecting Study participate in a study. Participants (Belmont Report) ✓ Excessive rewards from agreeing to participate. 1. Beneficence – Right to freedom from harm and discomfort 2.1 Human Dignity – Right to full disclosure The right to freedom from harm and Self-determination means that discomfort. prospective participants can voluntarily ✓ Obligation to avoid, prevent, or decide whether to take part in a study, minimize harm (nonmaleficence). without risk of prejudicial treatment. It can be physical, emotional, ✓ Also means that people have the social, or financial. right to ask questions, to refuse, to ✓ Researchers should be conducted give information and to withdraw only by qualified people. from the study. ✓ Sensitivity to psychological harm. A person’s right to self-determination The right to protection from exploitation. includes freedom from coercion. ✓ Study involvement should not ✓ Threats of penalty from failing to place participants at a participate in a study. disadvantage or expose them to ✓ Excessive rewards from agreeing damages. (Should I report it to to participate. authorities if I learned that my Concealment and deception participants are using illegal 3. Justice – Right to fair treatment drugs?) ✓ Study participants enter into a Justice concerns the equitable special relationship with distribution of benefits and burdens of researchers, and this relationship research. should never be exploited. (Role ✓ Vulnerable population must not be of a nurse-researchers – as a exploited. (Ex. those who cannot nurse? or as a researcher?) protect their own interest) 1989 (T.V.) 11 | JK  ✓ Neither neglect nor discriminate “You’re my Best friend” against individuals or groups who - You are in Love may benefit from research. (Ex. Minorities) ✓ Researchers must treat people who decline to participate or who withdraw from the study after initial agreement in a nonprejudicial manner. 3.1 Justice – Right to privacy Research is not more intrusive than it needs to be. Participants have the right to expect that their data will be kept in strictest confidence. Informed Consent - Means that participants have adequate information about the research, comprehend that information and have the ability to consent to or decline participation voluntarily. - Researchers usually documents informed consent by having participants sign a consent form. - Consent form should include information such as the purpose of the study, expectations regarding participation, voluntary nature of participation, and potential cause and benefits if there will be cause in participating in the study. Confidentiality Procedures - Anonymity – occurs when the researcher cannot link participants to their data. - Confidentiality in the absence of anonymity – a pledge that any information participants provide will not be publicly reported in a manner that identifies them and will not be accessible to others. 1989 (T.V.) 12 | JK  NCMB – 311: NURSING RESEARCH 1 1ST SEMESTER MIDTERMS 3RD YEAR NURSING WEEK 11 – Analysis of Qualitative and B. Facing the possibility of Premature Quantitative Data Death - Expediting the pursuit of key life Challenges of Qualitative Analysis milestones. - No universal rules for analyzing - Seeking ways to prolong life. qualitative data. Themes - Qualitative analysis requires an enormous amount of work. - Develop within categories of data. They - Reducing data for reporting purpose is emerge from the data. challenging. Theorizing Qualitative Analysis Process - Involves a systematic sorting of the data. - Process of fitting data together, of - Researchers develop alternative making the invisible obvious of linking explanations of the phenomenon and the and attributing consequences to hold these explanations up to determine antecedents. their fit with the data. - It is a process of conjecture and Recontextualizing verification of correction and modification of suggestion and defense. - Involves the further development of the theory such that its applicability to other Comprehending setting or groups is explored. - Making sense of the data and learning Qualitative Data Management and “what is going on” and preparing a Organization thorough description of the phenomenon. Transcribing Qualitative Data Categories - Audio-recorded interviews and field - Are underlying regularities, concepts and notes are major data sources in clusters of concepts. qualitative studies. Synthesizing - Verbatim transcription of the recordings is critical step in preparing for data - Involves sifting the data and putting analysis. pieces together. Researchers get a - Ensure accuracy and confirmability of the sense of what is typical with regard to the transcriptions. phenomenon and what variation is like. Developing a Coding Scheme 2 Levels of Synthesis: - Crucial in qualitative analysis is data A. Hoping for a Cure organization. - Delaying major life decisions and - Coding in qualitative data is reductionist. the pursuit of key milestone. - Waiting for and seeking out social cues that a cure is possible. 1989 (T.V.) 13 | JK 2 Types of Coding Scheme: the pattern formed by the confluence of meanings within individual accounts. Descriptive Coding Scheme – researchers whose aims are primarily Theme 3: Brining reverence to the birthing descriptive tend to use codes that are process and empowering women (Beck & fairly concrete. Watson, 2010) Conceptual Coding Scheme – studies A. Treated with respect that are designed to develop a theory are B. Pain relief taken seriously more likely to involve abstract, C. Communicated with labor and deliver conceptual categories. staff Coding Qualitative Data D. Reclaimed their body E. Strong sense of control Appearance of emerging codes during F. Birth plan was honored by labor and actual coding of qualitative data. delivery staff Qualitative data often do not proceed in a G. Mourned what they missed out with prior linear manner. birth How many individuals should code H. Healing subsequent birth but it can never qualitative data? change the past Analytic Procedures Miles and Huberman (1994) DeSantis and Ugarriza (2002) - Data Collection - Theme – is an abstract entity that brings - Data Reduction – refers to selecting, meaning and identity to a current focusing and simplifying abstracts and experience and its variant also transforming the data that appears manifestations. in a written field notes or transcriptions. - As such, a theme captures and unifies - Data Display – is organize, compress the nature or basic of the experience into and assembling of information that a meaningful whole. permits conclusion from being drawn and act. Spradley (1979) - Conclusion Drawing and Verification – - Similarity Principle – involves looking a conclusion has been made as we for units of information with similar collect and analyze data. content, symbols or meanings. - Contrast Principle – guides efforts to discover how content or symbols differ form other content or symbols. Ayres and Colleagues (2003) - Within-Case Analysis - Across-Case Analysis - Analysis of individual cases – enables the researcher to understand those aspect of experience that occur not as individual units of meaning but as part of 1989 (T.V.) 14 | JK  Data Analysis Frequency Polygon - Is the systematic organization and - Frequency distribution can be obtained synthesis of research data and in most graphically. quantitative studies. The testing of the - A distribution is said to be symmetrical in hypothesis using those data. shape, if when folder over, the two halves of a frequency polygon would be Quantitative Analysis superimposed. - The manipulation of numerical data Central Tendency through statistical procedures for the purpose of describing phenomenon or Mode assessing the magnitude and reliability of - That numerical value in a distribution that relationships among them. occurs most frequently. Purpose of Statistics - Ex. 50, 51, 51, 52, 53, 53, 53, 53, 54, 55, Summarize 56 Organize Median Evaluate Numeric Information Interpret - That point in a distribution above which Communicate and below which 50% of the subjects fall. - Ex. 2, 2, 3, 3, 4, 5, 6, 7, 8, 9 Branches of Statistics Mean - Descriptive Statistics – are used to describe and synthesize data obtained - The point on the score scale that is equal from empirical observations and to the sum of scores divided by the measurements. number of scores. It is also known as - Inferential Statistics – it is concerned average. with making decisions about a large body - Ex. 𝑋 = 85+109+120+135+158+177+181+195 8 = 145 of data in the population of interest by Variability using a sample of that universe. - A set of data can be summarized in terms Standard Deviations of 3 characteristics: - Captures the degree to which the scores ✓ Shape of distribution deviate from one another. It tells us how ✓ Central tendency much on average, the scores deviate ✓ Variability from the mean. Shape of Distribution - It also tells us the homogeneity or heterogeneity of the group. Frequency Distribution - The standard deviation is a variability - Is the systematic arrangement of index for a set of scores. It is also the numerical values from the lowest to the average of deviations from the mean. highest, together with a count of the Range number of times each value was obtained. - Is the highest score minus the lowest score. 1989 (T.V.) 15 | JK  Measurement Levels If p > a then the null hypothesis is accepted. Nominal “Every night with us is like a dream” - Lowest level; name categories; assignment of numbers to simply classify - New Romantics characteristics into categories. - Ex. 1 = male; 2 = female; 3 = others Ordinal - Attributes are ordered or ranked according to some criterion. - Ex. ability to perform ADLs; 1 = completely dependent; 2 = needs another person’s assistance; 3 = needs mechanical assistance; 4 = completely independent. Interval - Distance between the ranking can be specified. - Ex. a temperature of 60 Celsius us 10 Fahrenheit warmer than 50 Fahrenheit. Ratio - Highest scale; unlike intervals. - Ex. 200 pounds is twice as heavy as 100 pounds. Inferential Statistics Hypothesis Testing - Is based on negative inference. Hence the use of null hypothesis. - Researchers seek to reject the null hypothesis through various statistical tests. - The two most frequently used significance levels (referred to as alpha or a) are.05 and.01. - After the statistical test, look for the p- value computed then compare it to a level. If, p < a then the null hypothesis is rejected – the lower the p the more evidence we have to reject the null hypothesis. 1989 (T.V.) 16 | JK