Hydrogen azide, HN3, decomposes on heating by the following unbalanced reaction: HN3(g) 88n N2(g) 1 H2(g) If 3.0 atm of pure HN3(g) is decomposed initially, what is the final total pressure in the reaction container? What are the partial pressures of nitrogen and hydrogen gas? Assume the volume and temperature of the reaction container are constant

Week 9 Psyc: Scientific Research: (3/28, 3/30.4/1) I. Statistical Methods: -why is this important II. Two types of data: a. Quantitative data = numerical values (only focus on this type) i. Descriptive statistics ii. Inferential statistics b. Qualitative data = characteristics III. Descriptive Statistics: used to describe or summarize sets of data to make it more understandable. a. Ex: study of Schizophrenia: symptoms: delusions and hallucinations A. Types of Descriptive Statistics: a. Measurers of Central Tendency: mean, median, mode b. Measurers of Variability: how similar/different: Range and Standard deviation c. Correlation Coefficients: looking at the relationship of the values: Strong or Weak Ex: Schizophrenia: looking at the relationship between variables: #of people in family that have this disorder Schizophrenia: -variable 1: severity of symptoms : delusions, hallucinations -variable 2: # in a family Strong positive relationship between 2 variables +1.00 No relationship 0 Strong Negative relationship (inverse) - 1.00 Correlation Coefficients: continued -.85 -the value that tells about the strength of the relationship ( .85) -tells of the directing of the graph (negative or positive) (inverse or together) IV. Inferential Statistics: procedures for looking at probability that research results could derive from chance alone -you want your results to be real not just chance -inferential statistics enable researchers to be confident in drawing conclusion from their data A. Reading values: a. “p” = probability b. “r” = mean c. “t ” = analysis when wanting to compare means of 2 groups Ex: r = .60 = descriptive statistics (the strength and direction of 2 variables) p= .01 = inferential statistics (how confident are coefficient is in the experiment) p value determines how confident can be in the r value r value (mean) describes the degree of difference p value tells the significance of he degree of difference