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Transcript: Is there a relationship between women planning on serving a mission and the new missionary age change? Sarah Mellor, Nicole Westfall, Kira McCain Sufficient evidence to suggest that there is a significant relationship between the General Conference announcement concerning the change in missionary age and the number of women at BYU-Idaho deciding to serve missions. We would REJECT the null hypothesis that there is no relationship between the announcement made by Thomas S. Monson at General Conference and the number of women who are planning to serve on missions Test Statistic= 46.67 Degrees of Freedom= 4 P-value is approximately 0.000 (lower than 0.05) Introduction Continued During the October 2012 General Conference, Thomas S. Monson announced a change in missionary ages Changin' Ages Checking Requirements and Descriptive Statistics Sampling Method We don't have a Confidence Interval to Calculate Sampling Method: Simple Random Sample, Cluster Sample (SPSS simple random sample of all women's dorms) Sample Size Collected: 99 women 0% of nonresponse Introduction Checking requirements: Looking at the expected count, we can see that all of them are greater than five so the requirements are met. We have a large enough sample to determine a probable conclusion Convinience of new, lower age (less interference w/ job, schooling, relationships) Inferential Statistics Hypotheses: Ho= There is NO relationship between the mission age change and those planning to serve a mission. Ha= There IS a relationship between the mission age change and those planning on serving a mission. Descriptive statistics: % within Before and % within after. Pie chart Question Conclusion 5:00 class Further Study Template by Missing Link Images from Greater sample size Don't limit sample to those in the dorms


Transcript: STATISTICAL TECHNIQUES Observational study An example of an observational study is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case, the researchers would collect observations of both smokers and non-smokers, perhaps through a case-control study, and then look for the number of cases of lung cancer in each group. There are four main levels of measurement used in statistics: nominal, ordinal, interval, and ratio. Each of these have different degrees of usefulness in statistical research. Ratio measurements have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data. STEPS BIOSTATISTICS 1. Planning the Research 2. Designing the Experiments 3. Performing the Experiment 4. Further examining the data set in secondary analyses, to suggest new hypotheses for future study. 5. Documenting and presenting the results of the study An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead, data are gathered and correlations between predictors and response are investigated. Interval estimation 1 Experiments A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response. - to define normally - to test whether the difference between two populations, regarding a particular attribute is real or a chance of occurence - to study the correlation or association between two or more attributes in the same population - to evaluate the efficacy of vaccines, sera, etc. by control studies - to evaluate the achievements of public health programs - to fix priorities in public health programs USES Experimental and observational studies Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature. WHAT IS BIOSTATISTICS? Confidence intervals allow statisticians to express how closely the sample estimate matches the true value in the whole population. Often they are expressed as 95% confidence intervals. - statistics is the science of competing, classifying and tabulating numerical data and expressing results in a mathematical/ graphical data. - biostatistics is that branch of statistics concerned with mathematical facts and data relating to biological events. -is the application of statistics to problems in the biological sciences, health, and medicine. 3 Levels of measurement 2


Transcript: Anatomy Atlas ATHRAA AWAD Does it make a difference? Introduction Introduction Medical school Biological science what is anatomy atlas? what is anatomy atlas? A Detailed Ilustrated Images of the Human Body. Netter Atlas heart chambers It helps medical students to understand organs, bones, muscles, arteries, veins and nerves better. It illustrates each part of the body from different views and its relations to other parts and organs. The survey The survey A survey was completed by 15 medical students to gather data. We asked whether they used an atlas or not and if they did, which one? Voluntary. Experimental. Targeted population are people in the medical field. If medical students used an anatomy atlas they would get higher grades than those students who did not use it. Hypothesis Used 2-proportion test. response Of the 15 medical students, 10 students used the atlas with a range of grades between A's and B's. response While the 5 students remaining had grades between B's at most and lower. Also, different atlases were used, Netter's atlas was mostly used by 8 students, the rest are gray's atlas, Prof. Gaballah's atlas, and sameh doss. results results Analysis showed that students are 58% more likely to get an A if they use an atlas with 17% margin of error, and 43% more likely to get a C without using an atlas with 11% margin of error. The precentage of margin of error can be explained due to the the small sample size. Which atlas is best? Among the four atlases used by students, using the 2-prop test between two similar atlases, and th pair wise test between those two groups, analysis showed that it does not matter which atlas you use, as long as you use an atlas you will get higher grades. Which atlas is best? what I would do differently? Gather more data to reduce the margin of error. what I would do differently? Thoroughly test the atlases and compare them to each other better.


Transcript: Created by Allyson for Pre-Calc 12 Take-Out and Bio Statistics Take-Out Take-Out I chose the episode "Take-Out" where there are a series of robberies at different fancy restaurants. The mathematician, Charlie, must figure out a way to pin point the robber's next location. The Solution The Solution In order to bust the robbers, Charlie and the rest of the team must figure out a strategy that leads them to the next location the robbers will hit. One way to do that is to use probability and statistics. Probability -Probability is defined as "the measure of the likelihood that an event will occur. -In order to calculate the probability of something, you must divide the number of favorable (to the advantage of something) outcomes by the number of total outcomes. -To find probability in the episode "Take-Out" you would divide the number of restaurants the robbers are most likely to rob by the number of total restaurants in the area. Probability -Statistics is defined as the collection of data for interpretation and organization purposes. -In the episode, the investigation team collected data, which in this case was the reports of the robberies. -An example relating to the episode could be for instance, we select 10 restaurants out of 20 in the area, the average amount of money withheld at the restaurants would be an example of a statistic. Statistics Statistics Bio Statistics Bio Statistics Bio Statistics is the application of statistics to different aspects of biology, their job is to make sense of all of the data. Bio Statisticians are the ones who answer questions like "Does this new drug really work?", or "What causes cancer?" and even "How long is a person with said illness likely to survive?" A real life example of this, is professor Samuel Wasser who collected the data from the tusks and feces off of elephants to pinpoint where poaching happens in Africa. Calculating In order to calculate statistical data, you need to use this formula.


Transcript: Ho: Median <= zero HA: Median > zero C: when C> C.V. then do not reject null CV. of C: B.27 or page 786 in ZAR H0: A less than or equal to B HA: A > B Yes, the data seems to be normal. We have no reason to think otherwise. BIO STATISTICS Statistic H is determined by ranking all observations But, when N is too small use chisquared aprox test. H0: things are not dependent HA: things are dependent. aka one changes the other There are more than two categories. So, run a goodness of fit test. No, the data can not be paired. Rules for flow chart: First you must pick if you are testing central tendency or distribution. Pick the appropriate bracket. After that, there are questions on every slide. If the answer is yes to the question: then go LEFT. if the answer is no: go RIGHT. Used when several treatments are compared back to a single control example: drug A B and C compared to a control Yes, the data is nominal. So, run a Chi Squared Category Table. Tests for independence. Contingency Table Well, the data isnt normal. But it can still be paired. So, run a Wilcoxon Paired Sample T-Test Transform data: - Log >exponential -Square root > butted against zero Arcsine > percentage data ties: tied observations get mean ranks, they change possible outcomes Falls between Tukey and Dunnets as far as riskyness and Type 2 error Yes, one variable is in fact affecting another. Great, run a regression!! No, it is not nominal. Kolmogrov- Smirnov Test mean comparing a few pairs -two pairs: pairwise rate of 5% -so if you do too many - you're increasing your error No, the variances are unfortunately not equal. So, run a Welches Approximate T-Test. If there is a significant goodness of fit test you can do further comparisons (Sub Dividing) which indicated which category contributed to the significance. -This is exploratory Randomized Complete Block Design Yes, the variances are equal. So, run a Two Sample T-Test. p-value is significant!!! YAYAYAY are multi-comparisons planned (go left) or not (go right) Shoot. Is the data nominal? 2 SAMPLES Example where we did male vs. female and what was important in a relationship. No, I don't believe it is normally distributed. So, run the non parametric version of thr 1 way ANOVA, The Kruskal-Wallis Test or transform the data. report rsqu: coefficient of determination H0: b= 0 HA: b not equal 0 Awesome! There are 3 samples. How many factors are there? Yes, that data could be paired. But is it normal?? Student Newman Keuls No, the data is is not normal. So, run a Mann-Whitney Test. Yes it is normally distributed & there is only 1 factor. So run a 1-way ANOVA. multi-comparisons Yes, it is nominal. 1 SAMPLE H0: >= HA: < One or two tailed?? sample sizes testing distributions No parametric version test of continuous probability stats to compare a sample to a reference probability Also- plot twist: there are grouped KS as well! like the example we did in class that was Dry cat food to Wet cat food because there were 5 categories PS: if it is non-parametric then run a Spearman rank corr coeff. If significant p value: probs should do multi-comparisons There is more than 1 factor. So, a two-way ANOVA would be most appropriate. ps: there is not a non parametric version Is it nominal? Next question: could the data be paired? FISHERS LSD (least significant test) So run a one sample t-test if C > C.V. then reject null t.005,1,d.f.= chart C.V.: table B.3 page 678 in ZAR Mu: excel S (standard dev)= excel sxbar= s/squ of n t stat= graphpad 95 C.I.= graphpad d.f.= n-1 pvalue= graphad Tukey Test Rules: 1.) if n's are too small then calculated chi square os biased 2.) no expected freq should be < 1.0 3.) no more than 20% of observed should be less than 5.0 No, it shouldn't be normal. Planned= those you believe in advanced should show significant differences Is it normally distributed?? only used to analyze two or more categorical variables 1 If p=value is significant: probs should do multi- comparisions test. This is a sign ranked tests on the differences (d). H0: Median = HA: median does not equal ___ median= p= t0.05,1,n -> C.V.: B.12 or page 758 in ZAR t-: report the lesser of the two t-, t+ ^^^ 1. sort data from least to greatest 2. assign rank values based on median 3.if ties: average between the two HOW MANY SAMPLES ARE THERE? Dunnetts Test Yes, it can be paired and it is normal. So run a Paired Sample T-Test. PS: if you can pair, you should because it basically eliminates variability/"background noise" & increases the accuracy of the estimates YOU HAVE TO BE CONFIDENT YOUR DIFFERENCES ARE NORMALLY distributed -> is the n large enough? H0nutrients: MU 1 = _=_ =_=_ HA: at leave one is different H0: water H0 interaction ^^ three sets of hypotheses' YES, it is normal!! has a experiment wise error rate of 5%- conservative JB says toooo conservative.. like me lol but easy to do on JMP -this test just compares all means to each other How many categories are there? If main effects are significant that run

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