# CS4249 Cheat Sheet by eevyern

### Scales of Measur­ement

 Scale Desc­rip­tion Exam­ples Nomi­nal Caterg­orical; order doesn't matter Gender: 1 (male), 2 (female) Ordi­nal Ordered values. Order matters, but not difference between values Agree­ment: 1 (SD), 2 (D), 3 (Neutral), 4 (A), 5 (SA). Pain Scale (1-10) Inte­rval Numeric. Difference between values is meaningful Relative Temper­ature: °C, °F, pH Ratio Numeric. Zero and ratios are meaningful Height, Weight, Absolute Temper­ature (K)
Measur­ement is the process of observing and recording the observ­ations collected as a part of a research effort.

### Step 1: Define Research Questions

 eg. How does your techni­que... • Compare with altern­ative techni­ques? Tech­niq­ues • For which target popula­tion? Target users • For what tasks? Tasks • In terms of what measures? Perf­ormance measures • In what context? Other factors
Target users: need to be specific - students who have been using the desired medium consi­ste­ntly, for example
Perf­ormance measur­es: like speed, accuracy
Other factors: other than different techni­ques, what factors can influence the measures?

### Step 2: Define Variables

 IV • Factors manipu­lated in the experiment • Have multiple levels DV • Factors being measured Control variab­les • Attributes fixed throughout the experiment • Conf­oun­ders - attributes that vary and aren't accounted for Random variab­les • Attributes that are randomly sampled • Increases genera­lis­ability
Conf­oun­ders rather than IVs could have caused changes in DV.
They make it diffic­ult­/im­pos­sible to draw conclu­sions.
Order of presen­tation and prior experi­ence are two important confou­nders that we need to control. (by counte­r-b­ala­ncing and proper sampling)

### Step 3: Arranging Conditions (Withi­n-S­ubj­ects)

 List the IV and their levels eg. Technique (2 levels: Gesture, Marking) Menu depth (2 levels: 1, 2) Determine coun­ter­-ba­lancing strate­gies for each IV • Full counte­r-b­ala­ncing (n! condit­ions) • Latin Square (n condit­ions) • No counte­r-b­ala­ncing (seque­ntial) (1 condition) Determine minimum no. of partic­ipants Multiply all conditions together Determine fact­orial arrang­ement of conditions Put the permut­ations together Determine arrang­ement for each partic­ipant
Cond­ition reduction strate­gies:
• Pick the most import­ant­/in­ter­esting factors to test
• Run a few IVs at a time - if strong effect, include IV in future studies, otherwise, pick fixed control value for it

### One-way ANOVA

 Basic Idea: ANOVA tries to find the sources of this variance: • due to difference between groups • Variab­ility within each group Total Variab­ility = Betwee­nGroup + Within­Group 𝑆𝑆𝑇=­𝑆𝑆­𝑀+­𝑆𝑆𝑅 Ratio of Variab­ility F = (𝑆𝑆𝑀­/DFB) / (𝑆𝑆𝑅­/DFW) If the experiment is succ­ess­ful, then 𝑆𝑆𝑀>­𝑆𝑆𝑅. Betwee­n-group variab­ility will explain more variance than within­-group. The bigger the F value, the smaller the p value, and the less like the null hypothesis (no differ­ence) is true. Steps: 1. Calculate 𝑆𝑆𝑇 𝑆𝑆𝑇=­𝑠_𝑔­𝑟𝑎𝑛𝑑2 (𝑁−1) DFT = (N-1) 2. Calculate 𝑆𝑆𝑀 𝑆𝑆𝑀=∑_i𝑛_𝑖 (𝑥 ̅_𝑖­−𝑥 ­̅_𝑔𝑟𝑎𝑛𝑑 )2 • sum of n  difference of means from the grand mean DFM = (No. of groups - 1) 3. Calculate 𝑆𝑆𝑅 𝑆𝑆𝑅=∑_𝑖𝑠_𝑖2 (𝑛_𝑖−1) • sum of varianceno. of results in each group DFR = total no. of results - no. of groups Double check: 𝑆𝑆𝑇=­𝑆𝑆­𝑀+­𝑆𝑆𝑅 & DFT = DFM - DFR 4. Calculate Mean Squared Error MSM = SSM/­DFM MSR = SSR/­DFR 5. Calculate F-ratio F = MSM / MSR if F is lower than value in F-table, then p < 0.05  results are statis­tically signif­icant

### Behaviour Theories

 Health Belief Model Perceived Benefits v Perceived Barriers, Perceived Theat, Self-E­ffi­cacy, Cues to Action all contribute to Likelihood of Engaging in Health­-Pr­omoting Behaviour Theory of Reasoned Action Self-b­elief + Influenced beliefs, Attitudes, Intention  Behaviour Self-D­ete­rmi­nation Theory Intrinsic (self-­ben­efit) v Extrinsic motivation (external benefits) Goal Setting Theory Basic idea: goal serves as a motivator, work harder as long as they believe goal is achiev­able. Importance in Clarity, Challenge and Feedback Social Cognitive Theory Cognitive, Enviro­nmental and Behavi­oural factors determine human behaviour Fogg Behavi­oural Model Behaviour = Motiva­tors, Ability, Triggers • Motiva­tors: Sensation, Antici­pation, Social Cohesion • Ability: Train or Simplify • Triggers: Spark, Signal or Facili­tator

### Testable Research Questions

Weak questi­ons are untes­table and broad
Stronger questi­ons are more testable, but less genera­liz­able

### Step 4: Define Trials

 Estimate the time for each trial around 5-10 seconds? Estimate the time for each condit­ion Time for each trial  no. of trials for each condition Bala­nce the trials (so experiment is within 45 min) Combine with the cond­ition arrang­ement Essent­ially, find the total time the experiment will take
Trials: a single repetition of a single condition
Typically want to have at least 3 trials per condit­ion to increase reliab­ility
Consider time: trials should last for 45 minutes (excluding pre and post interv­iews)

### Cognition Processes

 Attention Perception Memory Learning Reading, speaking & listening Proble­m-s­olving, planning, reasoning & decisi­on-­making

### Attention

 Selecting things to concen­trate on at a point in time from the mass of stimuli around us Focus on inform­ation that's rele­vant to what we are doing Involves audio/­visual senses Design implic­ations: • Make inform­ation sali­ent if it needs attending to • make things stand out •avoid clutte­ring interface

### Perception

 How inform­ation is acqu­ired from the world, and transf­ormed into experi­ences Design repres­ent­ations that are readily percei­vable Implic­ation: • Group inform­ation • Text should bne legible and distin­gui­shable from the background

### Memory

 Stages of memory: • Encoding • Storage • Retrieval Encoding: • Determines which info is attended to in enviro­nment + how it's intepreted • Context affects extent to which info can be retrieved - different context  difficult to recall Implic­ations: • Focus attent­ion/no compli­cated procedures • Recogn­ition over recall • Provide various ways of encoding and retrieving info (searching v history) Storage: Sensory Memory: • shor­tes­t-t­erm memory, acts like a buffer for stimuli retrieved • Ability to remember and process info at same time • Inform­ation will decay within 10-15s • Extended by rehearsal, hindered by interf­erence Long-term Memory: •Decla­rative Memory (factual info): • Semantic Memory (general) + Episodic Memory (personal knowledge)• Procedural Memory (skill­s/h­abits) Retrieval: • Intern­al/­Ext­ernal stimuli for retr­ieval cues• Encoded at same time as memory

### Cognitive System Principles

 Unce­rtainty Princi­ple 𝑇=𝐼𝐶𝐻 where T = Decision time, H = log2(n+1) (where n is the no. of choices) Variable Rate Princi­ple More effort  Faster processing (ie. cycle time  Cycle time also diminishes with practice: 𝑇_𝑛=𝑇_1  𝑛−𝛼 Fitts' Law 𝑇_𝑀=𝑎+𝑏 log_2⁡­(𝐴/𝑊+1) where A = distance to target, W = error tolerance

### Trans-­the­ore­tical Models

 5 Stages of Change Pre-co­nte­mpl­ation, Contem­pla­tion, Prepar­ation, Action, Mainte­nance Processes of Change Consci­ousness raising, Social libera­tion, Goal setting, Helping relati­ons­hips, Rewards
Processes of change can be applied to 5 stages of change.
Each person will value different processes differ­ently.

### Statistics

 We use sample statistics to estima­te/­make infere­nces about population parameters Due to uncer­tainty and varia­bil­ity, conclu­sions and estimates may not always be correct. Need measures of reli­abi­lity • Conf­idence interval • the confidence that the true population value of a parameter falls within a conf­idence interval • affected by: vari­ation & sample size • Level of signif­ica­nce •“P value”, α • the prob. of reje­cting the null hypoth­esis when it is actually true (Type I error) • ie. concluding that there is a difference when there may be no actual difference • signifies the probab­ility that the difference is due to chance Level of Signif­icance Thre­sho­lds • Not signif­icant (p>.1; p=n.s.) • Marginally signif­icant (p<0.1) • (Fairly) signif­icant (p<.05) • (Good) signif­icant (p<.01) • (Excel­lently) signif­icant (p<.001)

### Central Limit Theorem

 As the sample size gets larger... The mean of sample means approaches the popu­lation mean The standard error of the sameple means = the standard deviation of the population mean 𝑆𝐸=𝑠/√𝑛=√(𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒/𝑛)

### 2-Sample t-test

 Small sample sizes  not normal distri­but­ion Use t-di­str­ibu­tion Steps: 1. Calculate mean difference 2. Calculate SD 3. Calculate no. of SDs away from 0 4. Calculate df = smaller n - 1 5. Calculate p-value, for signif­icance (which p-value is it closest to) If given desired conf­idence interv­al, steps: 1. Given desired CI 2. Get no. of SDs away from 0 from t-table 3. Calculate margin of error in units ((2)  SD) Difference between groups more likely to be signif­icant if: • Large differ­ence between means • Small SD or large n in each group Assump­tions: • Continuous variable • Indepe­ndent samples
Also called the inde­pen­den­t-s­amples t-test
Other tests:
• One-sample t-test (sample v constant)
• Paired­-sa­mpled t-test (withi­n-s­ubj­ects, repeated measures)
• One-way ANOVA

### Cognitive Heuristics

 Affe­cts where emot­ions influence deci­sions Avai­lab­ility where people over­est­imate the importance of inform­ation available to them Conf­irm­ation Bias where we only listen to inform­ation that confirms out prec­onc­ept­ions Halo Effect where an outcome in one area is due to factors from another Framing Effect where the words used push listeners in a certain direct­ion
Implic­ations: watch out for biasing your partic­ipants.

### Design Strategies for Lifestyle Behaviour Change

 Abstract & Reflective Unobtr­usive Public Aesthetic Positive Contro­llable Trendi­ng/­His­torical Compre­hensive

### Nielsen Heuristics

 Visibility of system status Match system and real world User control and freedom Consis­tency and standards Error prevention Recogn­ition over recall Flexib­ility and efficiency of use Aesthetic and minimalist design Help users recognise, diagnose, recover from errors Help and docume­ntation

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