A photon has a frequency of 6.0 3 104 Hz. (a) Convert this frequency into wavelength (nm). Does this frequency fall in the visible region? (b) Calculate the energy (in joules) of this photon. (c) Calculate the energy (in joules) of 1 mole of photons all with this frequency

Elementary Statistics Lecture 1 Definitions: Statistics-‐ the sciences of conducting studies to collect, organize, analyze, and draw conclusions from data • Variable-‐ A characteristic or attribute that can take on different values • Population-‐ All subjects to be studies • Sample-‐ A group of objects selected from the population • Descriptive-‐ Describe • Qualitative-‐ Distinct categories (good vs. bad) • Quantitative-‐ those that can be counted or measured • Discrete variables-‐ Assume values that can be counted (50-‐70 year olds) • Continuous variables-‐ Infinite number of values between any two specific values (height, weight, decimals, fractions) Boundaries-‐ Decrease the last number and add 5. Example: 5.55= 5.545 and 5.555 Keep the same number and add 5. • Nominal Level of Measurement-‐ Classifies data into mutually exclusive categories, in which no order or rankings may be assigned. (Zip code, eye color, nationality) • Ordinal Level of Measurement-‐ Data may be ranked, but precise differences between ranks do not exist (grades, 1 , 2 , 3 place) st nd rd • Interval Level of Measurement-‐ Ranks data and precise differences between measures exists, however there are no true zeros (IQ, temp, SAT scores) • Ratio Level of Measurement-‐ Just like interval but a true zero exists (height, weight, salary, age) • Random Sampling-‐ A sample in which all members of the population are equally likely to be chosen • Systematic Sampling-‐ A sample obtained by selecting every kth member of the population • Stratified Sampling-‐ Divide population into subgroups or strata, select subjects from each subject • Cluster Sample-‐ Divide population into sections of clusters and then use all members of that cluster in the sample • Convenience Sampling-‐ Ask who is convenient • Sampling error-‐ Difference between sample measures and the population measures • Non-‐sampling error-‐ Errors don’t have to do with your sample