Efnisyfirlit

• Cover Page
• Half Title page
• Title Page
• Copyright Page
• Dedication
• Contents
• List of figures
• List of tables
• Preface
• Illustration Credits
• Acknowledgements
• 1 Data, information and statistics
  • Introduction
  • The Nature of Data and Information
    • Abstraction and communication
    • Data types, variables, values and constants
    • Scales of measurement
    • Units of analysis
    • Independent and dependent variables
  • Parameters, Statistics and Samples
  • Statistics in Research
    • The normative paradigm
    • Research Design
    • General research issues
    • Survey research
    • Experimental research
    • Measurement issues
  • Misuse of Statistics
    • Naïve use
    • Intentional misuse of statistics
  • Summary
• 2 Using this book
  • Introduction
  • Guidance for Readers
    • Recommended use of material within different modules
    • Chapter structure
    • Slides
    • Exercises
    • Project exercises
  • SPSS
    • Comparing SPSS and Microsoft Excel
    • Creating an SPSS data sheet
    • Logical partitioning of a data sheet
    • Computing new variables
    • Notation
  • Equation Notation
    • Equations and expressions
    • Multiplication
    • Power
    • Arrays
    • Precedence of arithmetic operators
    • Magnitude
    • Set notation
    • Sums
    • Two uses of the bar accent
  • Summary
• 3 Descriptive statistics
  • Introduction
  • Descriptive Statistics for Nominal Variables
    • Frequency profiles and the mode
    • Example: European soccer cities
  • SPSS
    • Reporting results
  • Descriptive Statistics for Ordinal Variables
    • Median, minimum, maximum, lower and upper quartiles
    • Example: European soccer cities
  • SPSS
    • Reporting results
  • Descriptive Statistics for Interval and Ratio Variables
    • Mean, standard deviation, median, range and inter-quartile range
    • Example: European soccer cities
  • SPSS
    • Reporting results
  • Summary
  • Exercises
    • Exercise 3.1 Relative age in Grand Slam singles tennis
    • Exercise 3.2 Burnout potential in student athletes
    • Exercise 3.3. Fitness survey
  • Project Exercise
    • Exercise 3.4 Descriptive statistics for height and body mass of your class
• 4 Standardized scores
  • Introduction
  • Norms
  • Quantiles
    • Purpose
    • Example: English National Superleague Netball performance
  • SPSS
  • Z-Scores
    • Purpose
    • Example
  • T-Scores
    • Purpose
    • Example: Marathon running performance
  • Stanines
    • Purpose
    • Example: Male finishing times in the 2011 London Marathon
  • Summary
  • Exercises
    • Exercise 4.1 Deciles to interpret netball performance
    • Exercise 4.2 Quartiles for netball performance
    • Exercise 4.3. Decile norms for fitness test performances
    • Exercise 4.4 Using z-scores to compare running event performances
  • Project Exercise
    • Exercise 4.5 Fitness assessment
• 5 Probability
  • Introduction
  • Probability in Research
  • Experiments
    • Terminology
    • Multistep Experiments
    • Probability in multistep experiments
  • Assigning Probabilities
    • The classical method
    • The relative frequency method
    • The subjective method
  • Counting Rules
    • Complex sample spaces
    • Counting for combinations
    • Counting for permutations
  • Events and their Probabilities
    • Events
    • Rules for computing event probabilities
    • Events and set operations
    • Conditional probability
    • Dependent and independent events
  • Probabilistic Modelling
  • Summary
  • Exercises
    • Exercise 5.1 Probability of an experimental outcome
    • Exercise 5.2 Throwing two six-sided dice
    • Exercise 5.3 Retrospective probability in tennis
    • Exercise 5.4 Probabilistic modelling of a tennis point
    • Exercise 5.5 Combinations and permutations
  • Project Exercise
    • Exercise 5.6 Probability of upsets in sport
• 6 Data distributions
  • Introduction
  • Discrete Probability Distributions
    • The uniform discrete probability distribution
    • The binomial distribution
    • The Poisson distribution
  • Continuous Probability Distributions
    • The uniform continuous probability distribution
    • The normal probability distribution
    • T distributions
    • F distributions
    • Chi square distributions
  • Issues with Distributions
  • Summary
  • Exercises
    • Exercise 6.1 Probabilities and percentiles in a normal distribution
    • Exercise 6.2 Distribution of tennis performance variables in women's and men's singles
    • Exercise 6.3. English FA Premier League soccer
    • Exercise 6.4 Stanines
    • Exercise 6.5 Chance of winning the toss more than other teams
    • Exercise 6.6 Athletic burnout questionnaire
  • Project Exercise
    • Exercise 6.7 British Indoor Rowing performance
• 7 Hypothesis testing
  • Introduction
  • Hypotheses
    • The role of hypotheses in research studies
    • Qualities of hypotheses
  • Sampling
    • Populations and samples
    • A practical exercise in sampling
    • The coin tossing spreadsheet
  • Central Limit Theorem
    • A practical exercise sampling from a normally distributed population
    • Central Limit Theorem
  • Hypothesis Testing
  • Significance, Power and Effect
  • Selecting A Test
    • Single variable testing
    • Testing for relationships between variables
    • Testing for differences between independent groups
    • Testing for differences between conditions
    • Testing multiple dependent variables
    • Predictive modelling
    • Other statistical procedures
  • Summary
  • Exercises
    • Exercise 7.1 Determine the sampling distribution of mean
    • Exercise 7.2. Determine the confidence interval
    • Exercise 7.3 What test to use when?
  • Project Exercise
    • Exercise 7.4 Coin tossing exercise
• 8 Correlation
  • Introduction
  • Pearson's r
    • Purpose of the test
    • Coefficient of determination, r2
    • Example: Relationships between anthropometric measures and estimated V̇O2 max
    • SPSS
    • Presentation of results
  • Partial Correlations
    • Purpose of the test
    • Example: Confounding influence of distance covered by soccer players on the relationship between body mass and the number of path changes performed
    • SPSS
    • Presenting results
  • Non-Parametric Correlations
    • Purpose of the tests
    • SPSS
    • Presentation of results
  • Summary
  • Exercises
    • Exercise 8.1. Anthropometric variables and estimated V̇O2 max
    • Exercise 8.2. Variables related to margin of victory in soccer matches
    • Exercise 8.3. Serving in tennis
  • Project exercise
    • Exercise 8.4. Correlation between stature, body mass and estimated V̇O2 max
    • Exercise 8.5. Efficacy of World ranking in professional tennis
• 9 Linear Regression
  • Introduction
  • Bivariate Linear Regression
    • Purpose of the test
    • Interpolation and extrapolation
    • Uses of linear regression
    • Assumptions
    • Significance
    • Example: Middle distance running
    • SPSS
    • Presentation of results
  • Multiple Linear Regression
    • Purpose of the test
    • Assumptions
    • Significance
    • Example: Predicting the outcomes of international soccer matches
    • SPSS
    • Presentation of results
    • Stepwise and sequential methods
  • Summary
  • Exercises
    • Exercise 9.1. Predictive model of 3000m time in terms of 1500m time
    • Exercise 9.2. Multiple linear regression prediction of international soccer matches (knock out stages)
  • Project Exercise
    • Exercise 9.3. Relation between different event performances
    • Exercise 9.4. Performance prediction in rugby union
• 10 T-Tests
  • Introduction
  • The One-Sample T-Test
    • Purpose of the test
    • Assumptions
    • Example: Indoor rowing performances at national championships
    • SPSS
    • Reporting results
  • The Independent Samples T-Test
    • Purpose of the test
    • Assumptions
    • Example: A quasi-experimental study on the effectiveness of specific intermittent high intensity training
  • SPSS
    • Reporting results
  • The Paired Samples T-Test
    • Purpose of the test
    • Assumptions
    • Example: Effect of instructional and motivational self-talk on sit-up performance
    • SPSS
    • Reporting results
  • Summary
  • Exercises
    • Exercise 10.1. Specific training experiment
    • Exercise 10.2. Comparing the percentage of points won in tennis when the first serve is in and when a second serve is required
    • Exercise 10.3. Dominant vs non-dominant Y balance test
  • Project Exercise
    • Exercise 10.4. Gender effect on indoor rowing strategy
    • Exercise 10.5. Home advantage in soccer
• 11 Analysis of Variances
  • Introduction
  • The One-Way Anova Test
    • Purpose of the test
    • Assumptions
    • Example: Dietary intake of prepubescent female aesthetic athletes
    • SPSS
    • Presenting results
    • Bonferroni-adjusted, post hoc tests
    • The General Linear Model
  • Repeated Measures Anova
    • Purpose of the test
    • Assumptions
    • Example: Work-rate during different quarters of a netball match
    • SPSS
    • Presenting results
  • Analysis of Covariance (Ancova)
    • Purpose of the test
    • Assumptions
    • Example: 60m sprint time of team game athletes
    • SPSS
    • Presenting results
  • Random Factors
  • Summary
  • Exercises
    • Exercise 11.1. Body mass adjusted energy intake and protein, carbohydrate and fat within the diet of female prepubescent aesthetic athletes
    • Exercise 11.2. 400m hurdle performance
    • Exercise 11.3. Daily energy intake adjusted for body mass
  • Project Exercise
    • Exercise 11.4. Positional effect on the height of soccer players
• 12 Factorial ANOVA
  • Introduction
  • The Between–Between Design
    • Purpose of the test
    • Assumptions
    • Example: Children's activity in the playground during morning break
    • SPSS
  • Reporting Results
  • The Within–Within Desing
    • Purpose of the test
    • Assumptions
    • Example: Fluid loss with and without a wetsuit
    • SPSS
  • Reporting the Results
  • The Mixed Design
    • Purpose of the test
    • Assumptions
    • Example: Level and quarter effect on work-rate in netball
    • SPSS
    • Reporting the results
  • ANOVA Tests with more than Two Factors
  • Summary
  • Exercises
    • Exercise 12.1. Gender and age effect on playground activity at lunch time
    • Exercise 12.2. Gender and surface effect on inter-serve time in Grand Slam tennis
    • Exercise 12.3. Venue and period effect on work-rate in professional soccer
    • Exercise 12.4. 400m hurdles performance
    • Exercise 12.5. Three-way ANOVA with the soccer player tracking data
    • Exercise 12.6. Three-way ANOVA to analyse activity in the playground
  • Project Exercise
    • Exercise 12.7. Training and competition hours done by athletes in different types of sport
• 13 Multivariate ANOVA
  • Introduction
  • Single Factor MANOVA Tests (Between-Subjects Effects)
    • Purpose of the test
    • Assumptions
    • Example: Fitness testing of women's Gaelic footballers
    • SPSS
    • Reporting results
  • Factorial MANOVA Tests (Between-Subjects Effects)
    • Purpose
    • Assumptions
    • Example: Gender and sport type effect on burnout
    • SPSS
    • Reporting results
  • Repeated Measures MANOVA Tests
    • Purpose
    • Assumptions
    • Example: Comparing anxiety before training and competitive matches
    • SPSS
    • Reporting the results
  • Mixed Factorial MANOVA Tests
    • Purpose of the test
    • Assumptions
    • Example: Comparing anxiety before training and competitive matches
    • SPSS
    • Reporting the results
  • MANCOVA Tests
  • Summary
  • Exercises
    • Exercise 13.1. Effect of exercise participation on wellbeing
    • Exercise 13.2. Gender and type of sport effect on behavioural regulation in sport
    • Exercise 13.3. The effect of gender, type of sport and type of match on anxiety (modified SAS2)
  • Project Exercise
    • Exercise 13.4. Training and competition hours done by male and female athletes
• 14 Non-Parametric Tests
  • Introduction
  • Mann–Whitney U Test
    • Purpose of the test
    • Example: Comparing rally lengths between women's and men's Grand Slam singles tennis
    • SPSS
    • Presentation of results
  • Wilcoxon Signed Ranks Test
    • Purpose of the test
    • Example: Percentage of points won in tennis when the first serve is in and when a second serve is required
    • SPSS
    • Presentation of results
  • Kruskal–Wallis H Test
    • Purpose of the test
    • Assumptions
    • Example: Surface effect on rally duration in Grand Slam tournaments
    • SPSS
    • Presentation of results
  • Friedman test
    • Purpose of the test
    • Example: High-intensity activity performed during the four quarters of a netball match
    • SPSS
  • Summary
  • Exercises
    • Exercise 14.1. Service dominance in women's and men's singles tennis
    • Exercise 14.2. Burnout potential of individual sport and team sport athletes
    • Exercise 14.3. Comparing worry and somatic anxiety within student athletes
    • Exercise 14.4. Surface effect in men's and women's singles tennis
    • Exercise 14.5. Heart rate response during the four different quarters of club level netball matches
  • Project Exercise
    • Exercise 14.6. Home advantage in sport
    • Exercise 14.7. Surface effect on double faults played in Grand Slam singles tennis
    • Exercise 14.8. Preferred equipment for cardio-vascular exercise in the gym
• 15 Chi Square
  • Introduction
  • The chi square goodness of fit test
    • Purpose of the test
    • Assumptions
    • Example: Relative age in women's Grand Slam singles tennis
    • SPSS
    • Presentation of results
  • Chi Square Test of Independence
    • Purpose of the test
    • Assumptions
    • Example: Overseas players in Europe's ‘Big Four' soccer leagues
    • SPSS
    • Reporting results
  • Summary
  • Exercises
    • Exercise 15.1. Relative age in women's tennis
    • Exercise 15.2. Relative age in men's tennis
    • Exercise 15.3. Injuries in women's netball
  • Project Exercise
    • Exercise 15.4. Relative age of athletes
    • Exercise 15.5. Proportion of unseeded players in the 3rd round of Grand Slam tennis tournaments
• 16 Statistical Classification
  • Introduction
  • Discriminant Function Analysis
    • Purpose of the test
    • Assumptions
    • Example: Predicting outcomes of pool matches of the 2010 FIFA World Cup
    • SPSS and Excel
  • Binary Logistic Regression
    • Purpose of the test
    • Assumptions
    • Example: Predicting outcomes of the knockout matches of the 2010 FIFA World Cup
    • SPSS and Excel
  • Summary
  • Exercises
    • Exercise 16.1. FIFA World Cup 2010
    • Exercise 16.2. Violating the assumptions
    • Exercise 16.3. Satisfying assumption of no outliers in predictor variables
    • Exercise 16.4. Pre-tournament forecast
  • Project Exercise
    • Exercise 16.5. Predicting outcomes of soccer matches
    • Exercise 16.6. Predicting the outcomes of international rugby union matches
• 17 Cluster Analysis
  • Introduction
  • Hierarchical Cluster Analysis
    • Purpose of cluster analysis
    • Assumptions
    • First example: Score-line effect on net strategy in tennis
  • SPSS
    • Reporting results
    • Second example: Customer preference for a flavouring ingredient in energy drinks
  • SPSS
    • Reporting results
    • Discussion point
  • Summary
  • Exercise
    • Exercise 17.1. Athletes with different perceptions of anxiety
  • Project Exercise
    • Exercise 17.2. Perceived performance in different modules
• 18 Data Reduction Using Principal Components Analysis
  • Introduction
  • Principal Components Analysis
    • Purpose of principal components analysis
    • Assumptions
    • Example: Perceptions of sports tourism
  • SPSS
    • Using the component scores
    • Reporting results
  • Summary
  • Exercises
    • Exercise 18.1. Six component solution
  • Project Exercise
    • Exercise 18.2. Sports tourism
• 19 Reliability
  • Introduction
  • Measurement Issues
    • Validity
    • Objectivity
    • Reliability
  • Types Of Reliability Study
    • What is reliability?
    • Inter-rater reliability
    • Test–retest reliability
    • Parallel forms reliability
    • Internal consistency
  • Reliability Studies
  • Meaningful Reliability Assessment
  • Selecting Reliability Statistics
    • Factors
    • Multiple participant reliability studies
    • Multiple retest reliability studies
    • Single case reliability studies
    • Cross-validation
    • Internal consistency of components
  • Producing Reliability Statistics
    • Kappa
    • Weighted kappa
    • Correlation coefficients
    • Absolute error
    • Percentage error
    • Root mean squared error
    • Limits of agreement
    • Ninety-five per cent ratio limits of agreement
    • Change of the mean and standard error of measurement (typical error)
    • Coefficient of variation
    • Intraclass correlation coefficient
    • Cronbach's alpha
  • Summary
  • Exercises
    • Exercise 19.1. Kappa for agreement in netball performance assessment
    • Exercise 19.2. Kappa for decision accuracy in netball performance assessment
    • Exercise 19.3. Reliability of split times in middle distance athletics
    • Exercise 19.4. Y-Balance test performed with eyes open and using the non-dominant leg
    • Exercise 19.5. Scoring in amateur boxing
    • Exercise 19.6. Internal consistency of the Behavioural Regulation instrument (BRSQ)
    • Exercise 19.7. Internal consistency of a wellbeing construct
• 20 Statistical Power
  • Introduction
  • What Is Statistical Power?
  • Murphy et al.'s (2009) Model of Statistical Power
  • Four Applications of Power Analysis
    • Determining power levels
    • Determining sample size
    • Determining sensitivity of studies
    • Determining criteria for statistical significance
  • Summary
  • Exercises
    • Exercise 20.1. Desired relative seriousness
    • Exercise 20.2. Determining power for a training study
    • Exercise 20.3. Verifying observed power
    • Exercise 20.4. Power curves
  • Project Exercise
    • Exercise 20.5. Research project planning
• References
• Index

UM RAFBÆKUR Á HEIMKAUP.IS

Bókahillan þín er þitt svæði og þar eru bækurnar þínar geymdar. Þú kemst í bókahilluna þína hvar og hvenær sem er í tölvu eða snjalltæki. Einfalt og þægilegt!

Rafbók til eignar
Rafbók til eignar þarf að hlaða niður á þau tæki sem þú vilt nota innan eins árs frá því bókin er keypt.

Þú kemst í bækurnar hvar sem er
Þú getur nálgast allar raf(skóla)bækurnar þínar á einu augabragði, hvar og hvenær sem er í bókahillunni þinni. Engin taska, enginn kyndill og ekkert vesen (hvað þá yfirvigt).

Auðvelt að fletta og leita
Þú getur flakkað milli síðna og kafla eins og þér hentar best og farið beint í ákveðna kafla úr efnisyfirlitinu. Í leitinni finnur þú orð, kafla eða síður í einum smelli.

Glósur og yfirstrikanir
Þú getur auðkennt textabrot með mismunandi litum og skrifað glósur að vild í rafbókina. Þú getur jafnvel séð glósur og yfirstrikanir hjá bekkjarsystkinum og kennara ef þeir leyfa það. Allt á einum stað.

Hvað viltu sjá? / Þú ræður hvernig síðan lítur út
Þú lagar síðuna að þínum þörfum. Stækkaðu eða minnkaðu myndir og texta með multi-level zoom til að sjá síðuna eins og þér hentar best í þínu námi.



Fleiri góðir kostir
- Þú getur prentað síður úr bókinni (innan þeirra marka sem útgefandinn setur)
- Möguleiki á tengingu við annað stafrænt og gagnvirkt efni, svo sem myndbönd eða spurningar úr efninu
- Auðvelt að afrita og líma efni/texta fyrir t.d. heimaverkefni eða ritgerðir
- Styður tækni sem hjálpar nemendum með sjón- eða heyrnarskerðingu