(3,4 )This is the most versatile of statistical methods and can be used in many situations. After more than twenty years, Questia is discontinuing operations as of Monday, December 21, 2020. You can use the quantile() function to find quartiles in R. If your data is called data, then quantile(data, prob=c(.25,.5,.75), type=1) will return the three quartiles. For example, temperature in Celsius or Fahrenheit is at an interval scale because zero is not the lowest possible temperature. Whats the difference between relative frequency and probability? The table below gives some examples of how the units for variance compare to the units for standard deviation. A two-way ANOVA is a type of factorial ANOVA. The symbol for Standard Deviation is (the Greek letter sigma). That the relationship between the two variables is linear. Figure 11.1 gives some graphical representations of correlation. You can find all the citation styles and locales used in the Scribbr Citation Generator in our publicly accessible repository on Github. Having obtained the regression equation, calculate the residuals. A data set can often have no mode, one mode or more than one mode it all depends on how many different values repeat most frequently. That the scatter of points about the line is approximately constant we would not wish the variability of the dependent variable to be growing as the independent variable increases. It takes two arguments, CHISQ.TEST(observed_range, expected_range), and returns the p value. Imagine you want to know what the whole country thinks you can't ask millions of people, so instead you ask maybe 1,000 people. Variance is expressed in much larger units (e.g., meters squared). Relative Standard Deviation Formula (Table of Contents). Then you simply need to identify the most frequently occurring value. A statistically powerful test is more likely to reject a false negative (a Type II error). By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, Explore 1000+ varieties of Mock tests View more, Special Offer - All in One Financial Analyst Bundle (250+ Courses, 40+ Projects) Learn More, You can download this Relative Standard Deviation Template here , 250+ Online Courses | 40+ Projects | 1000+ Hours | Verifiable Certificates | Lifetime Access, All in One Financial Analyst Bundle- 250+ Courses, 40+ Projects, Investment Banking Course (123 Courses, 25+ Projects), Financial Modeling Course (7 Courses, 14 Projects), All in One Financial Analyst Bundle (250+ Courses, 40+ Projects), Examples of Relative Standard Deviation Formula (With Excel Template), Relative Standard Deviation Formula Calculator, How to Calculate Sharpe Ratio Using Formula, Relative Standard Deviation = (2.48 * 100) / 54, Relative Standard Deviation = (10 * 100) / 30, Relative Standard Deviation = (5 * 100) / 32. The data are given in table 11.1 and the scatter diagram shown in figure 11.2 Each dot represents one child, and it is placed at the point corresponding to the measurement of the height (horizontal axis) and the dead space (vertical axis). Divide the sum by the number of values in the data set. Standard deviation can be used to calculate a minimum and maximum value within which some aspect of the product should fall some high percentage of the time. Testing the combined effects of vaccination (vaccinated or not vaccinated) and health status (healthy or pre-existing condition) on the rate of flu infection in a population. Can I use a t-test to measure the difference among several groups? (Remember to exit from Stat mode.). Both types of estimates are important for gathering a clear idea of where a parameter is likely to lie. The level at which you measure a variable determines how you can analyze your data. Its best to remove outliers only when you have a sound reason for doing so. HTML | PDF | RSS In any dataset, theres usually some missing data. First, let us have some example values to work on: 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4. For example, the probability of a coin landing on heads is .5, meaning that if you flip the coin an infinite number of times, it will land on heads half the time. The empirical rule is a quick way to get an overview of your data and check for any outliers or extreme values that dont follow this pattern. They can also be rates (such as for speeds). As a result, the units match up in a sense. There are dozens of measures of effect sizes. The yield of the one does not seem to be dependent on the other in the sense that, on average, the height of a child depends on his age. In statistics, power refers to the likelihood of a hypothesis test detecting a true effect if there is one. Russell MAH, Cole PY, Idle MS, Adams L. Carbon monoxide yields of cigarettes and their relation to nicotine yield and type of filter. Standard deviation can have square units if the data values have square units (for example, an area in square feet). Only N-1 instead of N changes the calculations. If two variables are correlated are they causally related? When should I use the interquartile range? The blue-chip stock has a low standard deviation so that has low volatility. 7 . 140 Descriptive statistics summarize the characteristics of a data set. Some vehicles waive the initial charge and apply an exit charge instead. The correlation coefficient of 0.846 indicates a strong positive correlation between size of pulmonary anatomical dead space and height of child. What are the two types of probability distributions? Our team helps students graduate by offering: Scribbr specializes in editing study-related documents. The hypotheses youre testing with your experiment are: To calculate the expected values, you can make a Punnett square. In a well-designed study, the statistical hypotheses correspond logically to the research hypothesis. You should use the Pearson correlation coefficient when (1) the relationship is linear and (2) both variables are quantitative and (3) normally distributed and (4) have no outliers. Prisene p naturgass, kraftforsyning og raffinerte oljeprodukter kte alle fra oktober til november. As the degrees of freedom increase, Students t distribution becomes less leptokurtic, meaning that the probability of extreme values decreases. The test statistic you use will be determined by the statistical test. Prisindeks for frstegangsomsetning innenlands. Step 2: Multiply Step 1 by 100. NFL Week 13 December 05, 3:41 pm ET 1. Linear regression most often uses mean-square error (MSE) to calculate the error of the model. Standard error and standard deviation are both measures of variability. There are three main types of missing data. So both Standard Deviation vs Mean plays a vital role in the field of finance. Significant differences among group means are calculated using the F statistic, which is the ratio of the mean sum of squares (the variance explained by the independent variable) to the mean square error (the variance left over). The null hypothesis is that there is no association between them. As the line must be straight, it will probably pass through few, if any, of the dots. Standard deviation has units that are the same as the units for the data values. f: f 1, f 2, f 3, f n The formula for standard deviation becomes: They tell you how often a test statistic is expected to occur under the null hypothesis of the statistical test, based on where it falls in the null distribution. So both Standard Deviation vs Mean term is used in statistics for calculation purposes. For example, if you measure the weight of dogs in pounds, then the range would be given in pounds also. The confidence level is 95%. Quantitative variables can also be described by a frequency distribution, but first they need to be grouped into interval classes. This linear relationship is so certain that we can use mercury thermometers to measure temperature. The correlation coefficient is measured on a scale that varies from + 1 through 0 to 1. Consider a regression of blood pressure against age in middle aged men. Having put them on a scatter diagram, we simply draw the line through them. Standard deviation is easier to picture and apply. Plot a histogram and look at the shape of the bars. 11.2 Find the Spearman rank correlation for the data given in 11.1. Standard Deviation helps us to understand the value of the Group data; the variance of each data from the Group average. Because its based on values that come from the middle half of the distribution, its unlikely to be influenced by outliers. Deviation bars in Excel charts are a tool to show data variability and measurement accuracy. Notations for Standard Deviation. Calculate the Relative Standard Deviation for the following set of numbers: 8, 20, 40 and 60 where the standard deviation is 5. It sheds the volatility of historical volatility of that investment. You can use the QUARTILE() function to find quartiles in Excel. Download Relative Standard Deviation Template. Examples include: to allow for more than one predictor, age as well as height in the above example; to allow for covariates in a clinical trial the dependent variable may be outcome after treatment, the first independent variable can be binary, 0 for placebo and 1 for active treatment and the second independent variable may be a baseline variable, measured before treatment, but likely to affect outcome. The empirical rule, or the 68-95-99.7 rule, tells you where most of the values lie in a normal distribution: The empirical rule is a quick way to get an overview of your data and check for any outliers or extreme values that dont follow this pattern. The simple method of mean is to make the total of all data and divide it by the number of data, then we reach to mean. This number is called Eulers constant. It uses probabilities and models to test predictions about a population from sample data. The data can be classified into different categories within a variable. The standard deviation used for measuring the volatility of a stock. The test statistic will change based on the number of observations in your data, how variable your observations are, and how strong the underlying patterns in the data are. It is simply that the mortality rate from heart disease is inversely related and ice cream consumption positively related to a third factor, namely environmental temperature. So, does standard deviation have units? How is the error calculated in a linear regression model? We have to calculate the mean with the help of standard deviation. Thus, RSD eliminates the results which are too far in comparison with the actual RSD. Firstly always look at the scatter plot and ask, is it linear? When an investigator has collected two series of observations and wishes to see whether there is a relationship between them, he or she should first construct a scatter diagram. Whats the difference between standard deviation and variance? In both of these cases, you will also find a high p-value when you run your statistical test, meaning that your results could have occurred under the null hypothesis of no relationship between variables or no difference between groups. is the residual standard deviation, given by: This can be shown to be algebraically equal to. The t-distribution forms a bell curve when plotted on a graph. (What It Means), link to What To Consider When Choosing A College (9 Top Factors), you can learn about the difference between them here, a number of standard deviations above (or below) the mean. Missing data, or missing values, occur when you dont have data stored for certain variables or participants. the correlation between variables or difference between groups) divided by the variance in the data (i.e. The standard deviation used for measuring the volatility of a stock. No problem.Weare always here for you. When the two sets of observations increase or decrease together (positive) the line slopes upwards from left to right; when one set decreases as the other increases the line slopes downwards from left to right. The standard deviation used in for measuring volatility, so it is used for short-term analysis purposes. 3 These principles are set out in the ILO fundamental Conventions, No. A histogram is an effective way to tell if a frequency distribution appears to have a normal distribution. If the bars roughly follow a symmetrical bell or hill shape, like the example below, then the distribution is approximately normally distributed. 4 . Regn ut hvor mye prisene har endret seg. The median is the most informative measure of central tendency for skewed distributions or distributions with outliers. Stock A over the past 20 years had an average return of 10 percent, with a standard deviation of 20 percentage points (pp) and Stock B, over the same period, had average returns of 12 percent but a higher standard deviation of 30 pp. The vertical scale represents one set of measurements and the horizontal scale the other. Featured resources provide more information on special topics in adolescent health.. Adolescent Development Explained: Check out the OPA Adolescent Development Explained guide for information about the major developmental changes that occur in adolescence and how parents To calculate standard deviation from variance, take the square root. How do I test a hypothesis using the critical value of t? It can also be used to describe how far from the mean an observation is when the data follow a t-distribution. These are called true outliers. P kort sikt ventes en moderat nedgang i konomien, men BNP Fastland-Norge ansls likevel vre konjunkturnytral de neste rene. Mean is basically the simple average of data. Here we also discuss the standard Deviation vs Mean key differences with infographics and comparison table. That there is a linear relationship between them. Whats the difference between nominal and ordinal data? If you have a set of data points that measure the acceleration of an object (like a car) in meters per second squared (meters/second2), then the standard deviation would also be given in terms of meters per second squared (meters/second2). However, we later take the square root of the sum of squared differences, which returns us to the original units. How do I find a chi-square critical value in R? The alpha value, or the threshold for statistical significance, is arbitrary which value you use depends on your field of study. If your data does not meet these assumptions you might still be able to use a nonparametric statistical test, which have fewer requirements but also make weaker inferences. You can use the following Relative Standard Deviation Calculator, This is a guide to Relative Standard Deviation Formula. Together with the mean, standard deviation can tell us a lot about the data, and the units can also help us to understand the data. Find a distribution that matches the shape of your data and use that distribution to calculate the confidence interval. If the F statistic is higher than the critical value (the value of F that corresponds with your alpha value, usually 0.05), then the difference among groups is deemed statistically significant. These are the upper and lower bounds of the confidence interval. The part due to the dependence of one variable on the other is measured by Rho . Although the two tests are derived differently, they are algebraically equivalent, which makes intuitive sense. How do I perform a chi-square goodness of fit test in Excel? The Standard Deviation is a measure of how spread To test whether the association is merely apparent, and might have arisen by chance use the. To calculate standard deviation of a data set, first calculate the variance and then the square root of that. Correlation coefficients always range between -1 and 1. It is reasonable, for instance, to think of the height of children as dependent on age rather than the converse but consider a positive correlation between mean tar yield and nicotine yield of certain brands of cigarette. The nicotine liberated is unlikely to have its origin in the tar: both vary in parallel with some other factor or factors in the composition of the cigarettes. What happens to the shape of the chi-square distribution as the degrees of freedom (k) increase? You can use the qt() function to find the critical value of t in R. The function gives the critical value of t for the one-tailed test. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS. (What It Means) When we use statistics to analyze data, we often use mean (to find center) and where the tstatistic from has 13 degrees of freedom, and is equal to 2.160. l.033 2.160 x 0.18055 to l.033 + 2.160 x 0.18055 = 0.643 to 1.422. It enables us to predict y from x and gives us a better summary of the relationship between the two variables. So both the tool used for strategies which can be used for application in trading and investment activity. You can learn about when standard deviation is a percentage here. This is an important assumption of parametric statistical tests because they are sensitive to any dissimilarities. Standard deviation is calculated based on the mean. If, for a particular value of x, x i, the regression equation predicts a value of y fit , the prediction error is. All ANOVAs are designed to test for differences among three or more groups. Different returns from different fund houses indicate diversities and Investment dynamics. Multiply all values together to get their product. Dette gjorde at energiprisene samlet sett i PPI gikk opp med 9,6 prosent. Derived functions Complementary cumulative distribution function (tail distribution) Sometimes, it is useful to study the opposite question Which measures of central tendency can I use? A mean is basically the average of a set of two or more numbers. The Pearson correlation coefficient (r) is the most common way of measuring a linear correlation. If it truly had a Z-score of 103.333, it would be 103 standard deviations above the mean which is remarkably far out in the tail of the distribution! If your measurements, in pounds, were {25, 27, 33, 34, 40, 40, 41, 42, 50, 100}, then the range would be 100 25 = 75 pounds. The shape of a chi-square distribution depends on its degrees of freedom, k. The mean of a chi-square distribution is equal to its degrees of freedom (k) and the variance is 2k. The calculation of the correlation coefficient is as follows, with x representing the values of the independent variable (in this case height) and y representing the values of the dependent variable (in this case anatomical dead space). If it is categorical, sort the values by group, in any order. If you want the critical value of t for a two-tailed test, divide the significance level by two. The corresponding figures for the dependent variable can then be examined in relation to the increasing series for the independent variable. A part of the variation in one of the variables (as measured by its variance) can be thought of as being due to its relationship with the other variable and another part as due to undetermined (often random) causes. 11.3 If the values of x from the data in 11.1 represent mean distance of the area from the hospital and values of y represent attendance rates, what is the equation for the regression of y on x? If you have a set of data points that measure the acceleration of an object (like a car) in meters per second squared (meters/second2), then the variance would be given in terms of meters squared per second to the fourth (meters2/second4). No. We also assume that the association is linear, that one variable increases or decreases a fixed amount for a unit increase or decrease in the other. Statistical analysis is the main method for analyzing quantitative research data. The redshirt sophomore is the second quarterback to declare for this year's NFL draft. If you have a set of data points that measure the area of property (lots) in acres, then the standard deviation would also be given in terms of acres. How do I calculate the Pearson correlation coefficient in R? The intercept is often close to zero, but it would be wrong to conclude that this is a reliable estimate of the blood pressure in newly born male infants! The e in the Poisson distribution formula stands for the number 2.718. As a further example, a plot of monthly deaths from heart disease against monthly sales of ice cream would show a negative association. a t-value) is equivalent to the number of standard deviations away from the mean of the t-distribution. Whats the difference between standard error and standard deviation? When should I remove an outlier from my dataset? Regular standard deviation gives a fair idea about the distribution of scores around the mean (average). In normal distributions, a high standard deviation means that values are generally far from the mean, while a low standard deviation indicates that values are clustered close to the mean. If you have a set of data points that measure the area of a garden in square yards (yard2), then the variance would be given in terms of yard4. In most cases, researchers use an alpha of 0.05, which means that there is a less than 5% chance that the data being tested could have occurred under the null hypothesis. Thus, to streamline the particular fund according to his/her requirement, an ordinary man can approach RSD methods applied for Standard deviation. The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions. Can Standard Deviation Be A Percentage? In such cases it often does not matter which scale is put on which axis of the scatter diagram. Whats the difference between central tendency and variability? Staff Writer Since 2017 New York. The Akaike information criterion is a mathematical test used to evaluate how well a model fits the data it is meant to describe. If you flip a coin 1000 times and get 507 heads, the relative frequency, .507, is a good estimate of the probability. What is the difference between interval and ratio data? How to Calculate Variance from Standard Deviation? Statistical methods for assessing agreement between two methods of clinical measurement. In statistics, a model is the collection of one or more independent variables and their predicted interactions that researchers use to try to explain variation in their dependent variable. Nominal data is data that can be labelled or classified into mutually exclusive categories within a variable. They can also be estimated using p-value tables for the relevant test statistic. If you converted all of the data values to square feet (multiply acres by 43,560 to get feet), then the standard deviation would be given in terms of square feet. which is of use because we have calculated all the components of equation (11.2) in the calculation of the correlation coefficient. Generally, the test statistic is calculated as the pattern in your data (i.e. If one set of observations consists of experimental results and the other consists of a time scale or observed classification of some kind, it is usual to put the experimental results on the vertical axis. The relationship can be represented by a simple equation called the regression equation. There may or may not be a causative connection between the two correlated variables. This means your results may not be generalizable outside of your study because your data come from an unrepresentative sample. The z-score and t-score (aka z-value and t-value) show how many standard deviations away from the mean of the distribution you are, assuming your data follow a z-distribution or a t-distribution. In the case of the reverse situation i.e. However, a t test is used when you have a dependent quantitative variable and an independent categorical variable (with two groups). The alternative hypothesis is often abbreviated as Ha or H1. The geometric mean is often reported for financial indices and population growth rates. Population standard deviation calculator. You can use the chisq.test() function to perform a chi-square goodness of fit test in R. Give the observed values in the x argument, give the expected values in the p argument, and set rescale.p to true. A t-score (a.k.a. Statistical significance is a term used by researchers to state that it is unlikely their observations could have occurred under the null hypothesis of a statistical test. Some examples of factorial ANOVAs include: In ANOVA, the null hypothesis is that there is no difference among group means. Missing data are important because, depending on the type, they can sometimes bias your results. Suppose that you want to know if the genes for pea texture (R = round, r = wrinkled) and color (Y = yellow, y = green) are linked. To compare how well different models fit your data, you can use Akaikes information criterion for model selection. Well also compare units for standard deviation, mean, variance, and the data values themselves. What symbols are used to represent alternative hypotheses? More than one independent variable is possible in such a case the method is known as multiple regression. A conventional choice is to add noise with a standard deviation of / for a sample size n; this noise is often drawn from a Student-t distribution with n-1 degrees of freedom. Whats the difference between statistical and practical significance? Its the same technology used by dozens of other popular citation tools, including Mendeley and Zotero. Have a play with this at Normal Distribution Simulator. One of them is Relative Standard Formula which measures the probable demand at various stages based on historical statistical data and briefs about the expected production. If any value in the data set is zero, the geometric mean is zero. This confusion is a triumph of common sense over misleading terminology, because often each variable is dependent on some third variable, which may or may not be mentioned. What is the difference between a chi-square test and a t test? All that correlation shows is that the two variables are associated. How do I test the assumptions underlying linear regression? Statistics and Analytics has become the part and parcel of business houses and to forecast the expected demand of a particular data, a company is required to opt for different statistical tools. You can interpret the R as the proportion of variation in the dependent variable that is predicted by the statistical model. This table summarizes the most important differences between normal distributions and Poisson distributions: When the mean of a Poisson distribution is large (>10), it can be approximated by a normal distribution. , Prognoser for norsk og internasjonal konomi fram mot 2025 blir presentert fredag 9. desember klokken 09.00. Testing the effects of marital status (married, single, divorced, widowed), job status (employed, self-employed, unemployed, retired), and family history (no family history, some family history) on the incidence of depression in a population. Finally divide the numerator by the denominator. A plot of the data may reveal outlying points well away from the main body of the data, which could unduly influence the calculation of the correlation coefficient. To calculate the standard deviation of those numbers: The formula actually says all of that, and I will show you how. How do I decide which level of measurement to use? Add this value to the mean to calculate the upper limit of the confidence interval, and subtract this value from the mean to calculate the lower limit. Standard deviation is one of the key fundamental risk measures that analytics, portfolio managers, wealth management, and financial planner used. Using the sample we got: Sample Mean = 6.5, Sample Standard Deviation = 3.619 Our Sample Mean was wrong by 7%, and our Sample Standard Deviation was wrong by 21%. The formula depends on the type of estimate (e.g. a mean or a proportion) and on the distribution of your data. KPI-JAE steg 5,7 prosent samme periode. The formula for standard deviation below suggests how the squared and square root (radical) cancel each other out. For example, gender and ethnicity are always nominal level data because they cannot be ranked. Of course, standard deviation will always have the same units as the mean, since both are measured in the units for the data values. Relative Standard Deviation is calculated using the formula given below: Thus, the RSD for the above number is 4.6. We can still estimate the Standard Deviation. in. What do the sign and value of the correlation coefficient tell you? Oxford: Blackwell Scientific Publications, 1994:312-41. A one-way ANOVA has one independent variable, while a two-way ANOVA has two. Testing the effects of feed type (type A, B, or C) and barn crowding (not crowded, somewhat crowded, very crowded) on the final weight of chickens in a commercial farming operation. In contrast, the mean and mode can vary in skewed distributions. Statistical significance is arbitrary it depends on the threshold, or alpha value, chosen by the researcher. Why is the t distribution also called Students t distribution? There is a significant difference between the observed and expected genotypic frequencies (p < .05). Kalkulatoren er basert p konsumprisindeksen. Power is the extent to which a test can correctly detect a real effect when there is one. This is one of the major tools which indicates if the stock price is moving across the growth of the Business or not. A large effect size means that a research finding has practical significance, while a small effect size indicates limited practical applications. ), the calculated standard deviation will have units. How do I calculate a confidence interval if my data are not normally distributed? You can calculate the variance from standard deviation in a single step. There is a nice quote (possibly by Samuel Johnson): "You don't have to eat the whole animal to know that the meat is tough.". The way to draw the line is to take three values of x, one on the left side of the scatter diagram, one in the middle and one on the right, and substitute these in the equation, as follows: If x = 110, y = (1.033 x 110) 82.4 = 31.2, If x = 140, y = (1.033 x 140) 82.4 = 62.2, If x = 170, y = (1.033 x 170) 82.4 = 93.2. 20 What is the difference between a confidence interval and a confidence level? What are the assumptions of the Pearson correlation coefficient? How do I calculate a confidence interval of a mean using the critical value of t? If you convert the units for your data values, make sure to also report the standard deviation in the correct converted units! If you are only testing for a difference between two groups, use a t-test instead. A chi-square distribution is a continuous probability distribution. Around 95% of values are within 2 standard deviations of the mean. Standard deviation is basically used for the variability of data and frequently use to know the volatility of the stock. is the square root of . But in interpreting correlation it is important to remember that correlation is not causation. How do I perform a chi-square test of independence in R? If a curved line is needed to express the relationship, other and more complicated measures of the correlation must be used. In this case the paediatrician decides that a straight line can adequately describe the general trend of the dots. Maybe youre a senior and youre submitting Hi, I'm Jonathon. To reduce the Type I error probability, you can set a lower significance level. How do I calculate the Pearson correlation coefficient in Excel? How do I find the quartiles of a probability distribution? For example, the correlation coefficient for these data was 0.846. It is important to understand how standard deviation applies to data values that What To Consider When Choosing A College (9 Top Factors). Your study might not have the ability to answer your research question. How do you reduce the risk of making a Type II error? Relative Standard Deviation Formula Example #3. Statistical hypotheses always come in pairs: the null and alternative hypotheses. 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