PDF-Population Distribution by LGA

Mansakonko Kerewan Kuntaur Janjanbureh Banjul Kanifing Brikama Basse Cooking Fuel in 2003 Firewood Kerosene 02 Briquet 01 Charcoal 45 Liquified Propane Gas 4 ElectricitySolar 01 Saw Dust 05. Learning outcomes for today. Define a population and describe the attributes that make up that population. Describe the 3 types of population distribution. Work in a pair to learn about survivorship curves and age structure. Properties of Summary Statistics: Sampling Distribution. Main Theme . How can we use . math. to justify that our numerical . summaries from the sample are . good . summaries of the population?. Lecture Summary. Chapter . 15 . Notes. Parameters & Statistics. A . parameter. is a . number. that describes the population. The exact value of the parameter is usually unknown because we cannot examine the entire population.. Lan Kong. Associate . Professor. Division of Biostatistics and Bioinformatics. Department of Public Health . Sciences. December 15, . 2015. CTSI BERD Research Methods Seminar Series. Basic statistical concepts. 1. SAMPLING DISTRIBUTIONS —. SAMPLING DISTRIBUTIONS. Population and samples, parameters and statistics. A . POPULATION. is the set of . all possible subjects . of a given . experiment. or . study. Z-distribution. Central limit theorem. Sweet demonstration of the sampling distribution of the mean. Sweet data.  . R-code – sampling distribution exact. data.set <- c(6,4,5,3,10,3,5,3,6,5,4,8,7,2,8,5,8,5,4,0). Textbook: Sections . 8.7, 9.1 through 9.4. • Approximate binomial-distribution probabilities using a normal . distribution. • Explain statistical inference in terms of statistics and parameters.. @UWE_JT9. @. dave_lush. Scientific . Practice. The Binomial Distribution. This distribution can be seen when the outcomes have discrete values…. eg. rolling dice. Assumptions…. Fixed . number of . 24. Event A occurs with probability 0.1. Event B occurs with probability 0.6. If A and B are independent, then. a. P(A and B) = . 0.70. b. P(A or B) = 0.64.. c. . P(A and B) = . 0.64. d. . P(A or B) = 0.70.. Sample . statistics. will be slightly off from the true values of its population’s . parameters. Sampling error:. The difference between a sample statistic and a population parameter. Probability theory. Main Theme . How can we use . math. to justify that our numerical . summaries from the sample are . good . summaries of the population?. Lecture Summary. Today, we focus on two summary statistics of the sample and study its theoretical properties. DEF - (Population pyramid. ). is two back-to-back bar graphs, one showing the number of males and one showing females in a particular population in five-year age groups. . This is important because you can tell from the age distribution important characteristic of a country, whether high guest worker population, they just had a war or a deadly disease and more. . Section 7.1 . What Is a Sampling Distribution?. After this section, you should be able to…. DISTINGUISH between a parameter and a statistic. DEFINE sampling distribution. DISTINGUISH between population distribution, sampling distribution, and the distribution of sample data. Penny for your thoughts Take a sample of size 5 from the population Calculate p = the proportion of pennies minted in the 2000s Calculate the mean year of the pennies as well KEEP THIS DATA WHERE YOU CAN USE IT AGAIN!