סטטיסטיקה לתלמידי תקשורת 63-014-01/02/03 שם המרצה :ד"ר ש .פרידקין שנה :ב' סוג הקורס :קורס חובה ,תואר ראשון ,הרצאה ותרגיל היקף שעות 3 :ש"ס 1.5 ,ש"ש שנת לימודים :תשע"ה סמסטר :א' שעות קבלה :יום ג' 12:00-11:00 משרד :בניין ,109חדר 4 טל'03-5317035 : דוא"לshimon.fridkin@gmail.com : א .תיאור הקורס ומטרתו: הקורס נועד להקנות מושגים וכלים סטטיסטיים בסיסיים במטרה לאפשר ניתוח נתונים עצמאי וקריאה ביקורתית של ספרות מקצועית בתחומי התקשורת השונים .הקורס מציג ומדגים שימושים מתחומי הסטטיסטיקה התיאורית וההיסקית לצורך ניתוח ,פירוש והצגת נתונים. ב .שיטה: הקורס מבוסס על הרצאה ותרגיל שבועיים .במהלך הקורס הסטודנט יקבל כלים ,הן בתיאוריה והן ביישום מעשי בעזרת מחשב ,לביצוע ניתוחים כמותיים-סטטיסטיים במדעי החברה בכלל ובתקשורת בפרט .בתרגיל ,המשתתפים יתרגלו חומר שנלמד בהרצאה שתקדם לו כולל פתרון שאלות שיילקחו בעיקר מתחום המחקר הכמותי בתקשורת. חלק ניכר מהתרגילים יוקדש ללמידה ושימוש בתוכנת העיבודים הסטטיסטיים .SPSSפרטים מלאים והנחיות ימסרו בקבוצות התרגול. ג .דרישות הקורס: .1שימוש במחשבון מדעי CASIO-991לצורך חישובים סטטיסטיים במהלך הקורס. .2השתתפות פעילה בשיעורים ובתרגילים. .3קריאת פרטי החובה לקראת כל שיעור. .4הגשת 2סוגים של מטלות: ( )Iמטלות בכל מפגש-תרגיל, ( )IIעבודת מחקר בתקשורת (ביצוע ניתוחים סטטיסטיים באמצעות SPSSוכתיבת ממצאי המחקר) אשר יש להגיש לא מאוחר משבועיים לאחר תום הקורס .העבודה תוגש באמצעות מערכת ה .Moodleבמסגרת העבודה יש להגיש קבצים הבאים: Word file, Syntax file, Output file, SPSS file. .5מבחן. סטודנטים שלא יגישו את התרגילים במועדים שנקבעו ללא סיבה מוצדקת ,לא יורשו לגשת למבחן המסכם. הרכב הציון הסופי: הגשת מטלות בכל מפגש-תרגול –.10% הגשת עבודה מסכמת אשר יש להגיש לא מאוחר משבועיים לאחר תום הקורס – .20% מבחן – .70% ד .חומרי קריאה: Books: Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. שמור לפי )2386011( HAY 1 Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. )2382828( REI שמור לפי Morgan, G. A., Leech, N. L., Gloeckner, G. W. & Barrett, K. C. (2011). SPSS for introductory and intermediate statistics: IBM SPSS for introductory statistics: Use and interpretation. (4th ed). New York: Taylor & Francis. אין Articles: Neuman, W. R., Guggenheim, L., Jang, S. M., & Bae, S. Y. (2014). The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data. Journal of Communication, 64(2), 193–214. )155002( כתב עת אלקטרוני Shaw, A., & Hill, B. M. (2014). Laboratories of Oligarchy? How the Iron Law Extends to Peer Production. Journal of Communication, 64(2), 215–238. )155002( כתב עת אלקטרוני Jungher, A. (2014). The Logic of Political Coverage on Twitter: Temporal Dynamics and Content. Journal of Communication, 64(2), 239–259. )155002( כתב עת אלקטרוני Giglietto, F., & Selva, D. (2014). Second Screen and Participation: A Content Analysis on a Full Season Dataset of Tweets. Journal of Communication, 64(2), 260–277. )155002( כתב עת אלקטרוני Emery, S. L., Szczypka, G., Abril, E. P., Kim, Y., & Vera, L. (2014). Are You Scared Yet? Evaluating Fear Appeal Messages in Tweets about the Tips Campaign. Journal of Communication, 64(2), 278–295. )155002( כתב עת אלקטרוני Vargo, C. J., Guo, L., McCombs, M., & Shaw, D. L. (2014). Network Issue Agendas on Twitter During the 2012 U.S. Presidential Election. Journal of Communication, 64(2), 296–316. )155002( כתב עת אלקטרוני Park, J., Baek, Y. M., & Cha, M. (2014). Cross-Cultural Comparison of Nonverbal Cues in Emoticons on Twitter: Evidence from Big Data Analysis. Journal of Communication, 64(2), 333– 354. )155002( כתב עת אלקטרוני Knobloch-Westerwick, S., & Crane, J. (2012). A losing battle: Effects of prolonged-exposure to thin ideal images on dieting and body satisfaction. Communication Research, 39, 79-102. )141113( כתב עת אלקטרוני Knobloch-Westerwick, S., & Hoplamazian, G. J. (2012). Gendering the self: Selective magazine reading and reinforcement of gender conformity. Communication Research, 39, 358-384. )141113( כתב עת אלקטרוני Velez, J. A., Mahood, C., Ewoldsen, D. R., & Moyer-Gusé, E. (2014). Ingroup Versus Outgroup Conflict in the Context of Violent Video Game Play: The Effect of Cooperation on Increased Helping and Decreased Aggression. Communication Research, 41(5), 607-626. )141113( כתב עת אלקטרוני Custers, K., & Van den Bulck, J. (2013). The Cultivation of Fear of Sexual Violence in Women: Processes and Moderators of the Relationship between Television and Fear. Communication Research, 40(1), 96-124. )141113( כתב עת אלקטרוני 2 Fu, W. W. (2013). National Audience Tastes in Hollywood Film Genres: Cultural Distance and Linguistic Affinity. Communication Research, 40(6), 789-817. )141113( כתב עת אלקטרוני Lee, N-J., Shah, D. V., & McLeod, J. M. (2013). Processes of Political Socialization: A Communication Mediation Approach to Youth Civic Engagement. Communication Research, 40(5), 669-697. )141113( כתב עת אלקטרוני נושאים ורשימת קריאה.ו סטטיסטיקה ומדעי תקשורת.1 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Statistics and Communication Science (pp. 1-16) - Statistics and Communication Science; Why Do Science?; Assumptions and Philosophies of Scientific Investigation; Building Your Statistical Vocabulary; The Role of Statistics in Scientific Investigation] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Using Statistics to Conduct Quantitative Research (pp. 1-16) - A World of Statistics; Why Do Quantitative Research?; Typical Steps Involved in Quantitative Research] יסודות של מדידה בתקשורת.2 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Fundamentals of Measurement (pp. 16-30) - Methods of Measurement: Operationalization; Levels of Measurement; Measurement Precision; Qualitative Data versus Quantitative Measurement; Measurement Quality: Reliability of Measurement;Validity of Measurement] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Using Statistics to Conduct Quantitative Research (pp. 17-27) - Collecting Data on Variables; Variables and Hypotheses; Measurement of Variables] דגימה.3 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Sampling (pp.31-44) - Population Inference; The Literary Digest Poll: Population Inference Gone Awry; Population Inference Through Representativeness; Sampling Methods:Nonprobability Sampling; Probability Sampling; Is Nonprobability Sampling Really So Bad?] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Using Statistics to Conduct Quantitative Research (pp. 28-42) - Sampling] תיאורים גרפיים וטבלאיים של נתונים.4 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Data Description and Visualization (pp. 45-50) - Graphical and Tabular Descriptions of Data; Frequency Tables; The Histogram; Describing the Shape of a Distribution; Another Graphical Tool: The Box Plot (pp. 60-61)] מדדי נטייה מרכזית.5 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Measures of Central Tendency (pp. 51-55) - The Mode; The Median; The Arithmetic Mean; Choosing a Measure of Central Tendency] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Central Tendency (pp. 45-60) - Doing a Study and Reporting Descriptive Information; Typical Measures of Central Tendency; Relations among Mean, Median, and Mode] מדדי השתנות ופיזור.6 3 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Measures of Variation (pp. 56-59) - The Range and Interquartile Range; The Standard Deviation; The Variance; Quantifying Skewness and Kurtosis (pp. 59-60); Standardization (pp. 61-63)] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Looking at Variability and Dispersion (pp. 61-86) - Assessing Dispersion; The Relationship between Measures of Central Tendency and Variability; Examining Distributions] יסודות הסתברות.7 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Fundamentals of Probability (pp. 83-102) - Defining Probability; Laws of Probability; The Additive Law of Probability; The Multiplicative Law of Probability; Probability Distributions; The Binomial Probability Distribution; The Normal Probability Distribution; Chebyshev's Theorem; Random Variables and Expected Values] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Examining Distributions (pp. 74-86)] הערכה וכימות מהימנות.8 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Assessing and Quantifying Reliability (pp. 103-129) - Classical Test Theory; Partioning Measurements into Their Components; The Definition of Reliability Under Classical Test Theory; Estimating the Reliability of Quantitative Measurements; Estimating Reliability From Repeated Measurements Over Time; Estimating Reliability From Internal Consistency of Indicator Scores; Reliability of Method or of Measurement?; Reliability of Subjective Categorical Judgments; Holsti's Method; Correcting for Chance; Agreement: Scott's π and Cohen's k; Using an Agreement lndex; How High is High Enough?] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Ensuring Reliability and Validity (pp. 117-142) - The Notion of Measurement Acceptability; How to Do a Study of Measurement Adequacy; Reliability; Validity; The Relation of Validity to Reliability] אומדן פרמטרים.9 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Parameter Estimation (pp. 130-157) - The Theory of Estimation;The Sampling Distribution;Properties of the Sampling Distribution of the Sample Mean;Deriving the Probability of Obtaining Certain Sample Means Interval Estimates; The Confidence Interval ;A More Realistic Approach to Interval Estimation; The Relationship Between Confidence and Precision; Computing the Probability of a Sample Mean, Revisited ;Interval Estimates Derived From Samples of Convenience;Estimating a Population Proportion; Bootstrapping a Confidence lnterval] בדיקת השערות.10 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Hypothesis Testing Concepts (pp. 158-182) - Hypothesis Testing Steps:Step 1: Tlanslate the Research Hypothesis or Question into statistical Hypothesis;Step 2: Quantify the Obtained Result; Step 3: Derive the p value ;Step 4: Decide Between the Null and Alternative Hypothesis; Step 5: Interpret the Result of the Test in Substantive Terms; Testing a Hypothesis About a Population Proportion; Testing a Nondirectional ("Two-tailed") Hypothesis; Testing a Directional ("One-tailed") Hypothesis; Decision Errors, Power, and Validity; Type I, Type II, and Type III errors; The Validity and Power of a Statistical Test; Hypothesis Test or Confidence Interval?] מתאם.11 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Describing Association Between Quantitative Variables (pp. 63-82) - Pearson's Coefficient of Correlation; Alternative Measures of Association;Cautions When Interpreting Correlation;Visualizing Correlation: The Scatterplot; Descriptively Comparing Groups;Data Screening and Missing Data; Introducing Some Common Symbolic Notation] 4 Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Correlations (pp. 87-116) - The Notion of Correlation; Elements of the Correlation; Computing the Pearson Product-Moment Correlation; Matters Affecting Correlations; Methods of Correlations; Alternative Forms of Association] השוואת ממוצעים.12 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Testing a Hypothesis About a Single Mean (pp. 183-209):The One-Samplet test ;Testing a Directional Hypothesis About a Single Mean ;Testing a Nondirectional Hypothesis ;Conducting the One-Sample t test With a Computer ;Statistical Assumptions ;Large Versus Small Samples ;Confidence lntervals ;Bootstrapping the p value ;Comparing the Means of Paired Responses ;The Paired-Samples t test;Paired-Sample Inference From Nonrandom Samples;Comparing Two Independent Groups (pp. 210-243): The Independent Groups t test ;The Pooled Variance Approach;The Welch-Satterthwaite Approach;The Conditional Decision Rule ;The Behrens-Fisher Problem ;Violations of the Normality Assumption;Confidence Intervals for the Mean Difference ;Bootstrapping Confidence Intervals and p-values ;Effect Size ;Testing for Group Differences in Variability;Levene’s Test ;The Brown-Forsythe Test ;The F-ratio Test: A Test to Avoid ;Comparing Two Groups from Nonrandom Samples;The Random Assignment Model of Chance ;Inference Without Random Sampling or Random Assignment;Thinking Clearly About Inference;Comparing Two Independent Proportions] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Statistical Significance Hypothesis (pp. 143-178): Testing When Comparing Two Means: Doing a Study That Tests a Hypothesis of Differences Between Means; Assumptions in Parametric Hypothesis Testing; Comparing Sample and Population Means; Comparing the Means of Two Sample Groups: The Two-Sample r Test; Comparing Means Differences of Paired Scores: The Paired Difference t; Assessing Power] ניתוח שונות.13 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Single Factor Analysis of Variance (pp. 366-407): Analysisof Variance: Partitioning the Outcome Variable into its Sources of Variation; Total, Between-, and Within-Group Variability in Y; The F ratio; Underlying Statistical Theory; Statistical Assumptions of ANOVA; Revisiting the Pooled Variance t test; Quantifying Effect Size; Why Not Multiple t tests?; Inference with Nonrandom Samples; Pairwise Mean Comparisons; The Multiple Test Problem Resurfaces; The Bonferroni Correction; Holm’s Sequential Rejection Method; The Games-Howell Method; Using a Pooled Error Term; Focused Contrasts; Focused t tests; Contrast Coefficients; Scheffe’s Test; Some Controversies in the Comparison of Multiple Groups; Planned Versus Unplanned Comparisons: To Correct or Not?; Are We A Bit Fickle About The Multiple Test Problem?; Do We Really Need ANOVA?] Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Comparing More Than Two Means (pp. 179-246): One-Way Analysis of Variance; Hypothesis Testing for More Than Two Means; The Analysis of Variance Hypothesis Test; What After ANOVA? Multiple Comparison Tests; Extensions of Analysis of Variance; Factorial Analysis of Variance; Doing a Study That Involves More Than One Independent Variable; Types of Effects to Test; Computing the Fixed-Effect ANOVA; Random and Mixed-Effects Designs] רגרסיה.14 Hayes, A. F. (2012). Statistical methods for communication science. New York: Routledge. [Simple Linear Regression (pp. 271-309): The Simple Linear Regression Model; The Simple Regression Line; The Least Squares Criterion; The Standard Error of Estimation; The Standardized Regression Equation; Variance Explained by a Regression Model ; More on Residuals; The Dangers of Extrapolating Away From the Data; Population Inference in Linear Regression; Testing a Hypothesis About the Population Regression Weight; Confidence Intervals for β; Reframing Inference In Terms of the Population Correlation; Statistical Assumptions; Inference in Nonrandom Samples: The Permutation Test; Detecting Influential Cases; Distance, Leverage, and Influence; Influence as Change in the Model When a Case is Excluded] 5 Reinard, J. (2006). Communication research statistics. Thousand Oaks, CA: Sage. [Multiple Regression Correlation (pp. 345-380): Contrasting Bivariate Correlation and Multiple Regression Correlation; Components of Multiple Correlations; How to Do a Multiple Regression Correlation Study] 6